library(dplyr)
library(tidyverse)
library(knitr)
library(plotly)
library(kableExtra)
library(leaflet)
library(RColorBrewer)

1 Introduction

2 Domain knowledge

2.1 Grennhouse Gases (GHG)

2.1.1 Definition

  • Greenhouse gases constitute a group of gases contributing to global warming and climate change.
  • Greenhouse gases are gases that trap heat in the atmosphere.
  • Without greenhouse gases, the average temperature of Earth’s surface would be about -18° rather than the present average of 15°.
  • Atmospheric concentrations are determined by the balance between sources (emissions of the gas from human activities and natural systems) and sinks (the removal of the gas from the atmosphere by conversion to a different chemical compound or absorption by bodies of water).

2.1.2 List

The primary greenhouse gases in Earth’s atmosphere are water vapor (H2O), carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O) and ozone (O3).

-Carbon dioxide (CO2):

  • Carbon dioxide enters the atmosphere through burning fossil fuels (coal, natural gas, and oil), solid waste, trees and other biological materials, and also as a result of certain chemical reactions (e.g., manufacture of cement).
  • Carbon dioxide is removed from the atmosphere (or “sequesterd”) when it is absorbed by plants as part of the biological carbon cycle.

-Methane (CH4):

  • Methane is emitted during the production and transport of coal, natural gas, and oil. Methane emissions also result from livestock and other agricultural practices.

-Nitrous oxide (N2O):

  • Nitrous oxide is emitted during agricultural and industrial activities, combustion of fossil fuels and solid waste, as well as during treatment of wastewater.

-Fluorinated gases:

  • Hydrofluocarbons, perfluocarbons, sulfur hexafluoride, and nitrogen trfluoride are synthetic, powerful greenhouse gases that are emitted from a variety of industrial processes. These gases are typically emitted in sammer quantities, but because they are potent greenhouse gases, they are sometimes referred to as high Global Warming Potential gase

2.1.3 Sources

  • The vast majority of anthropogenic carbon dioxide emissions come from combustion of fossil fuels, principally coal, oil and natural gas, with additional contributions coming from deforestation and other changes in land use.

2.1.4 Global Warming Potential

GHGs warm the earth by absorbing energy and slowing the rate at which the energy escapes to space. Different GHGs can have different effects on the earth’s warming depending on their ability to absorb energy (radiative efficiency) and how long they stay in the atmosphere (lifetime).

The Global Warming Potential was developed to allow comparisons of the global warming impacts of different gases. It is a measure of how much energy the emission of 1 ton of a gas will absorb over a given period of time, relative to the emissions of 1 ton of carbon dioxide. The larger the GWP, the more that given gas warms the earth compared to CO2 over that time period (usually 100 years). GWP provides a common unit of measure which allows analysts to add up emissions estimates of different gases (e.g., to compile a national GHG inventory), and allows policymakers to compare emissions reduction opportunities across sectors.

  • CO2, by definition, has a GWP of 1 regardless of the time period used since it is the gas used as the reference. CO2 emissions cause an increase in the atmospheric concentrations that will least thousands of years.

  • Methane (CH4) is estimated to have a GWP of 28-36 over 100 years. CH4 emitted today lasts about a decade on average, which is much less time thanCO2. But CH4 absorbs much more energy than CO2.

  • Nitrous Oxide (N2O) has a GWP 265-298 times that of CO2 for a 100-year timescale. BO2 emitted today remains in the atmosphere for more than 100 years, on average.

  • Fluorinated gases are high-GWP gases because, for a given amount of mass, they trap substantially more than CO2. The GWPs for these gases can be in the thousands or tens of thousands.

2.2 GHG inventory and assessment

A GHG assessment is an evaluation of the quantity of emitted (or captured and stored) GHGs in the atmosphere over one year resulting from the activities of an organization or a territory.

2.2.1 Methodology

The methodological princiles vary considerably depending on the type of assessment that is carried out.

  • GHG organizational reporting (companies, collectivities, public establishments)
  • GHG reporting for territories

The Chapter 8 of the IPCC report provides framewsork and guidance for reporting complete, consistent and transparent national greeenhouse gas inventories, regardless the method used to produce the data.

2.2.2 Geographical Coverage

  • The 2006 Guidelines are designed to estimate and report on national inventories of anthropogenic greenhouse gas emissions and removels. Anthropogenic emissions and removeals means that greenhouse gas emissions and removals in national inventories are a result of human activities.

  • National inventories should include ghg emissions and removals taking place withing national territory and offshore areas over whoch the country has jurisdication.

2.2.3 gases included

The 2006 Guidelines can be applied for two groups of greenhouse gases:

  • GHG covered by the Montreal Protocol: carbon dioxide, methane, nitrous oxide, hydroflurocarbons, perfluorocarbons…
  • Other halogenated greenhouse gases not covered by the Montreal Protocol

2.2.4 Sectors and categories

The 2006 Guidelines group emissions and removals categories into five main sectors:

  • Energy
  • Industrial Processes and Product Use (IPPU)
  • Agriculture, Forestry and Other Land Use (AFOLU)
  • Waste
  • Other

These sectors are divided into several sub-categories with specific codes that can be explored in [the chapter 8.5 of the guideline](https://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/1_Volume1/V1_8_Ch8_Reporting_Guidance.pdf].

2.2.5 Scopes

The Greenhouse Protocol provides accounting and reporting standards, sector guidance, calculation tools, and training for businesses and governement. It establishs a comprenhensive, global, standardized framework for measuring and managing emissions from private and public sector operations. The Greenhouse gas Protocol divides emissions into 3 scopes:

  • Scope 1: Direct GHG emissions

Scope 1 covers all direct GHG emissions by a company. It includes fuel combustion, company and fugitive emissions.

  • Scope 2: Electricity indirect GHG emissions

Scope 2 covers indirect GHG emissions from consumption of purchased electricity, heat or steam.

  • Scope 1: Other indirect GHG emissions

Scope 3 covers other indirect emissions, such as the extraction and production of purchased materials and fuels, transport-related activities in vehicles not owned or controlled by the reporting entity, electricity-related activities (e.g. transmission and distribution (T&D) losses) not covered in Scope 2, outsourced activities, waste disposal, etc. Scope 3 emissions (also known as value chain emissions) often represent the largest source of greenhouse gas emissions and in some cases can account for up to 90% of the total carbon impact.

2.2.6 Frameworks

2.2.6.1 Bilan carbone

In France, ADEME published in 2004 a methodology for quantifying greenhouse gas emissions for organizations, called the Bilan Carbone®. This method is today coordinated and dissiminated by the Association Bilan carbone.

The Bilan Carbone® method takes account of all greenhouse gases defined by the IPCC for all physical flows without which the organization could not function. This method therefore allows companies and territorial collectivities to carry out a global assessment of GHG emissions, whether direct or indirect. A method has been specifically developed on the territorial scale.

2.2.6.2 GHG Protocol

In 1998, the World Business Council for Sustainable Development (WBCSD) and the World Resources Institutes (WRI) developed, in partnership with companies, NGOs and State representatives, the GHG Protocol: “A Corporate Accounting and Reporting Standard”.

This protocol, extensively disseminated internationally, served as the basis for drafting ISO 14064-1:2006.

In October 2011, the GHG Protocol was supplemented by the “Corporate Value Chain (Scope 3) Accounting and Reporting Standard”, which details in particular the potential indirect GHG emission categories for an organization.

Since July 2014, a method dedicated to Territories has been made available: the Global Protocol for Community-scale GHG emissions.

2.3 Glossary

2.3.1 Carbon Budget

  • A carbon budget is an upper limit of total CO2 emissions associated with remaining below a specific global average - temperature.

  • Global emissions budgets are calculated according to historical cumulative emissions from fossil, industrial processes, and land use change, but vary according to the global temperature target that is chosen, the probability of staying below that target, and the emissions of other non CO2 greenhouse gases.

  • Emissions budgets are relevant to climate change mitigation because they indicate a finite amount of carbon dioxide that can be emitted over time, before resulting in dangerous levels of global warming.

3 Data cartography

3.1 Data providers & producers

3.1.1 World scale

3.1.1.1 The world Bank

3.1.1.2 World Resources Institute

  • CAIT - Historical Emissions Data:

CAIT Historic allow for easy access, analysis and visualization of the latest available international greenhouse gas emissions data. It includes information for 191 countries and the European Union, 50 U.S. states, 6 gases, multiple economic sectors, and 160 years - carbon dioxide emissions for 1850-2014 and multi-sector greenhouse gas emission for 1990-2014.

More description is available here

3.1.1.3 Our World In Data

3.1.1.4 PIK

3.1.1.5 The United Nations Framework Convention on Climate Change (UNFCCC)

  • History:

  • The UNFCCC is an international environmental treaty addressing climate change, negotiated by 154 states at tht United Nations Conference on Environment and Development, informally known as the Earth Summit, held in Rio de Janiero in 1992.

  • The Climate Change Convention entered into force on 21 March 1994. Adopted in 1992 at the Rio Earth Summit, most members of the Organization for Economic Cooperation and Development (OECD) plus the states of Central and Eastern Europe - known collectively as Annex I countries - are committed to adopting policies and measures aimed at returning their greenhouse-gas emissions to 1990 levels by the year 2000. All Parties develop and submit “national communications” containing inventories of greenhouse gas emissions by source and greenhouse gas removals by sinks.

  • Objectives:

    • The UNFCCC seeks for the stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic human-induced interferences with the earth’s climate system.
    • Definition guidelines for submitting annual national greenhouse gas emissions inventories
    • The GHG data displayed on the UNFCC website are data from official submissions of GHG emissions/removals data by countries that are Parties to the Climate Change Convention.

  • Parties:

The Convention divides countries into three main groups according to differing commitments. Here is the description of these categories (source).

-Annex I Parties include the Industrialized  countries that were members of the OECD (Organization for Economic Co-operation and Development) in 1992, plus countries with economies in transition (the EIT parties), including the Russian Federation, the Baltic States, and several Central and Eastern European States.

-Annex II Parties consist of the OECD members of Annex I, but not the EIT Parties. They are required to provide financial resources to enable developing countries to undertake emissions reduction activities under the Convention and to help them adapt to adverse effects of climate change.

- Non-Annex I Parties are mostly developing countries. Certain groups of developing countries are recognized by the Convention as being especially vulnerable to the adverse impacts of climate change, including countries with low-lying coastal areas and those prone to desertification and drought. Others (such as countries that rely heavily on income from fossil fuel production and commerce) feel more vulnerable to the potential economic impacts of climate change response measures.

3.1.2 Europe scale

3.1.2.1 European Environmental Agency

3.1.2.2 Eurostat

3.1.3 National & sub-national scale (France use case)

3.1.3.1 ADEME

3.1.3.2 Citepa

3.2 Datasets

Data provider Data sets Geoscale Data source
The World Bank GHG emissions indicators World scale Country scale
The World Resources Institute - CAIT dataset World scale Country scale
The World Resources Institute - UNFCCC dataset World scale Country scale
The World Resources Institute - PIK dataset World scale Country scale
UNFCCC World scale Country scale
PIK World scale Country scale
OECD OECD scale Country scale OECD.Stat
European Environmental Agency Europe scale Country scale
Our World In Data CO2 emissions data World scale Country scale
Global Carbon Project CO2 emissions data World scale;Country scale; City scale
ADEME Carbon footprint City scale
Citepa GHG emissions data Country scale; City scale
Carbon Disclosure Project GHG emissions data City scale

3.3 data modeling

We propose a data model for mapping the various data source identified

Column name Type Description
data.source string
data.provider string
geo.scale string
geo.code.iso2c string
geo.code.iso3c string
geo.name string
year numeric
sector string
gas string
value numeric
unit string 
# create dataset
OGS_ghg_emission = data.frame(data.source = as.character(),
                              data.provider = as.character(),
                              geo.scale = as.character(),
                              geo.code.iso2c = as.character(),
                              geo.code.iso3c = as.character(),
                              geo.name = as.character(),
                              year = as.numeric(),
                              sector = as.character(),
                              gas = as.character(),
                              value = as.numeric(),
                              unit = as.character())

4 World scale

4.1 Data sources exploration

4.1.1 World Bank

4.1.1.1 Data description

The World Bank provides access to several indicators related to GHG emissions. This data is provided through API or by download.

In the example below, we will use the R package WDI, which provides easy access to World Bank indicators as shwon in the table below.

library(WDI)
 
# get datasets on emissions

datasets_emissions = as.data.frame(WDIsearch("emissions"))

# Show datasets on emissions
datasets_emissions  %>% 
  kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover"), full_width = F, font_size = 13) %>% 
  scroll_box(width = "100%", height = "400px")
indicator name
EE.BOD.CGLS.ZS Water pollution, clay and glass industry (% of total BOD emissions)
EE.BOD.CHEM.ZS Water pollution, chemical industry (% of total BOD emissions)
EE.BOD.FOOD.ZS Water pollution, food industry (% of total BOD emissions)
EE.BOD.MTAL.ZS Water pollution, metal industry (% of total BOD emissions)
EE.BOD.OTHR.ZS Water pollution, other industry (% of total BOD emissions)
EE.BOD.PAPR.ZS Water pollution, paper and pulp industry (% of total BOD emissions)
EE.BOD.TOTL.KG Organic water pollutant (BOD) emissions (kg per day)
EE.BOD.TXTL.ZS Water pollution, textile industry (% of total BOD emissions)
EE.BOD.WOOD.ZS Water pollution, wood industry (% of total BOD emissions)
EE.BOD.WRKR.KG Organic water pollutant (BOD) emissions (kg per day per worker)
EN.ATM.CO2E.CP.KT CO2 emissions from cement production (thousand metric tons)
EN.ATM.CO2E.FF.KT CO2 emissions from fossil-fuels, total (thousand metric tons)
EN.ATM.CO2E.FF.ZS CO2 emissions from fossil-fuels (% of total)
EN.ATM.CO2E.GDP CO2 emissions, industrial (kg per 1987 US$ of GDP)
EN.ATM.CO2E.GF.KT CO2 emissions from gaseous fuel consumption (kt)
EN.ATM.CO2E.GF.ZS CO2 emissions from gaseous fuel consumption (% of total)
EN.ATM.CO2E.GL.KT CO2 emissions from gas flaring (thousand metric tons)
EN.ATM.CO2E.KD.87.GD CO2 emissions, industrial (kg per 1987 US$ of GDP)
EN.ATM.CO2E.KD.GD CO2 emissions (kg per 2010 US$ of GDP)
EN.ATM.CO2E.KT CO2 emissions (kt)
EN.ATM.CO2E.LF.KT CO2 emissions from liquid fuel consumption (kt)
EN.ATM.CO2E.LF.ZS CO2 emissions from liquid fuel consumption (% of total)
EN.ATM.CO2E.PC CO2 emissions (metric tons per capita)
EN.ATM.CO2E.PP.GD CO2 emissions (kg per PPP $ of GDP)
EN.ATM.CO2E.PP.GD.KD CO2 emissions (kg per 2017 PPP $ of GDP)
EN.ATM.CO2E.SF.KT CO2 emissions from solid fuel consumption (kt)
EN.ATM.CO2E.SF.ZS CO2 emissions from solid fuel consumption (% of total)
EN.ATM.GHGO.KT.CE Other greenhouse gas emissions, HFC, PFC and SF6 (thousand metric tons of CO2 equivalent)
EN.ATM.GHGO.ZG Other greenhouse gas emissions (% change from 1990)
EN.ATM.GHGT.KT.CE Total greenhouse gas emissions (kt of CO2 equivalent)
EN.ATM.GHGT.ZG Total greenhouse gas emissions (% change from 1990)
EN.ATM.HFCG.KT.CE HFC gas emissions (thousand metric tons of CO2 equivalent)
EN.ATM.METH.AG.KT.CE Agricultural methane emissions (thousand metric tons of CO2 equivalent)
EN.ATM.METH.AG.ZS Agricultural methane emissions (% of total)
EN.ATM.METH.EG.KT.CE Methane emissions in energy sector (thousand metric tons of CO2 equivalent)
EN.ATM.METH.EG.ZS Energy related methane emissions (% of total)
EN.ATM.METH.IN.ZS Energy related methane emissions (% of total)
EN.ATM.METH.KT.CE Methane emissions (kt of CO2 equivalent)
EN.ATM.METH.PC Methane emissions (kt of CO2 equivalent per capita)
EN.ATM.METH.ZG Methane emissions (% change from 1990)
EN.ATM.NOXE.AG.KT.CE Agricultural nitrous oxide emissions (thousand metric tons of CO2 equivalent)
EN.ATM.NOXE.AG.ZS Agricultural nitrous oxide emissions (% of total)
EN.ATM.NOXE.EG.KT.CE Nitrous oxide emissions in energy sector (thousand metric tons of CO2 equivalent)
EN.ATM.NOXE.EG.ZS Nitrous oxide emissions in energy sector (% of total)
EN.ATM.NOXE.EI.ZS Nitrous oxide emissions in industrial and energy processes (% of total nitrous oxide emissions)
EN.ATM.NOXE.IN.KT.CE Industrial nitrous oxide emissions (thousand metric tons of CO2 equivalent)
EN.ATM.NOXE.IN.ZS Nitrous oxide emissions in industrial and energy processes (% of total nitrous oxide emissions)
EN.ATM.NOXE.KT.CE Nitrous oxide emissions (thousand metric tons of CO2 equivalent)
EN.ATM.NOXE.MT.CE Nitrous oxide emissions (metric tons of CO2 equivalent)
EN.ATM.NOXE.PC Nitrous oxide emissions (metric tons of CO2 equivalent per capita)
EN.ATM.NOXE.ZG Nitrous oxide emissions (% change from 1990)
EN.ATM.PFCG.KT.CE PFC gas emissions (thousand metric tons of CO2 equivalent)
EN.ATM.SF6G.KT.CE SF6 gas emissions (thousand metric tons of CO2 equivalent)
EN.CLC.GHGR.MT.CE GHG net emissions/removals by LUCF (Mt of CO2 equivalent)
EN.CO2.BLDG.MT CO2 emissions from residential buildings and commercial and public services (million metric tons)
EN.CO2.BLDG.ZS CO2 emissions from residential buildings and commercial and public services (% of total fuel combustion)
EN.CO2.ETOT.MT CO2 emissions from electricity and heat production, total (million metric tons)
EN.CO2.ETOT.ZS CO2 emissions from electricity and heat production, total (% of total fuel combustion)
EN.CO2.MANF.MT CO2 emissions from manufacturing industries and construction (million metric tons)
EN.CO2.MANF.ZS CO2 emissions from manufacturing industries and construction (% of total fuel combustion)
EN.CO2.OTHX.MT CO2 emissions from other sectors, excluding residential buildings and commercial and public services (million metric tons)
EN.CO2.OTHX.ZS CO2 emissions from other sectors, excluding residential buildings and commercial and public services (% of total fuel combustion)
EN.CO2.TRAN.MT CO2 emissions from transport (million metric tons)
EN.CO2.TRAN.ZS CO2 emissions from transport (% of total fuel combustion)

We will select for this article the indicator EN.ATM.GHGT.KT.CE, which corresponds to the total greenhouse gas emissions (measured in kt of CO2 equivalent).

# get Total greenhouse gas emissions (kt of CO2 equivalent)
ghg_emissions_wb = WDI(indicator='EN.ATM.GHGT.KT.CE')

# Show data sample 
ghg_emissions_wb %>% 
  filter(country == "World") %>% 
  kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover"), full_width = F, font_size = 13) %>% 
  scroll_box(width = "100%", height = "400px")
iso2c country EN.ATM.GHGT.KT.CE year
1W World NA 2020
1W World NA 2019
1W World NA 2018
1W World NA 2017
1W World NA 2016
1W World NA 2015
1W World NA 2014
1W World NA 2013
1W World 53526303 2012
1W World 52790527 2011
1W World 50911114 2010
1W World 48150621 2009
1W World 48664441 2008
1W World 49977387 2007
1W World 48639988 2006
1W World 47216059 2005
1W World 45658898 2004
1W World 44422305 2003
1W World 43070575 2002
1W World 40365673 2001
1W World 40563437 2000
1W World 40891983 1999
1W World 44048271 1998
1W World 43375208 1997
1W World 39258545 1996
1W World 39040328 1995
1W World 38810307 1994
1W World 38081370 1993
1W World 39824355 1992
1W World 38587504 1991
1W World 38232170 1990
1W World 36108992 1989
1W World 35478326 1988
1W World 35963102 1987
1W World 34049392 1986
1W World 33080641 1985
1W World 32822992 1984
1W World 33852269 1983
1W World 34370124 1982
1W World 32418039 1981
1W World 33480327 1980
1W World 33615148 1979
1W World 32120464 1978
1W World 31553905 1977
1W World 30301514 1976
1W World 28860203 1975
1W World 28434027 1974
1W World 29107899 1973
1W World 28148781 1972
1W World 26263241 1971
1W World 27660218 1970
1W World NA 1969
1W World NA 1968
1W World NA 1967
1W World NA 1966
1W World NA 1965
1W World NA 1964
1W World NA 1963
1W World NA 1962
1W World NA 1961
1W World NA 1960

4.1.1.2 Data mapping

# Mapping function
OGS.MAP.WB = function(Worldbank_data, start_date, end_date, geoscale, geoname.filter){
  Worldbank_data_OGS = Worldbank_data %>% 
    add_column(data.source = "World.Bank",
               data.provider = "World.Bank",
               geo.scale = geoscale,
               sector = "All",
               gas = "All",
               geo.code.iso3c = NA,
               unit = "MtCO₂e") %>% 
    rename(geo.code.iso2c = iso2c,
           geo.name = country,
           value = EN.ATM.GHGT.KT.CE) %>% 
    select(data.source, data.provider, geo.scale, geo.code.iso2c, geo.code.iso3c, geo.name,
           year, sector, gas, value) %>% 
    filter(year >= start_date & year <= end_date) %>% 
    filter(geo.name == geoname.filter) %>%
    mutate(value = value * 0.001)
  
  return(Worldbank_data_OGS)
}

# mapping data
Worldbank_data_OGS = OGS.MAP.WB(Worldbank_data = ghg_emissions_wb,
                                start_date = 1970,
                                end_date = 2012,
                                geoscale = "World",
                                geoname.filter = "World" )

# plot timeserie
Worldbank_data_OGS %>% 
  plot_ly() %>% 
  add_trace(y = ~value, 
            x = ~year, 
            type = 'scatter',
            mode = 'lines+markers',
            orientation = "v",
            hoverinfo = 'text',
            text = ~paste('</br> Year: ', year,
                          '</br> Value: ', value,
                          '</br> Gas: ', gas,
                          '</br> Sector: ', sector,
                          '</br> Source: ', data.provider)) %>% 
  layout(title = "World GHG emissions (source: WRI - CAIT)",
         yaxis = list(title = "GHG emissions"), 
         xaxis = list(title = "Years"))

4.1.2 World Resources Institute

The World Resources Institute compile various sources of GHG emissions and provide access to this data through a specific tool: CLIMAT WATCH. Climate Watch enables the exploration of historical GHG emissions data, downnload and collection via a specified API.

# load data
ghg_emissions_wri = read.csv("https://raw.githubusercontent.com/OpenGeoScales/CarbonData/feature-article/datasets/raw/wri/historical_emissions/historical_emissions.csv", 
                             encoding = "UTF-8")

Historic emission data is provided in wide format and contains emissions for various sectors and gases. The table below describes the data content.

Column Description
Country The country name
Data.source Five data sources: CAIT, PIK, GCP, UNFCCC_AI, UNFCCC_NAI
Sector 30 categories of sectors: Total including LUCF,Total excluding LUCF, Total fossil fuels and cement, Electricity/Heat, Coal, Oil…
Gas 8 categories of sectors: All GHG,KYOTOGHG, CO2, Aggregate GHGs, CH4, N2O, F-Gas , Aggregate F-gases
Unit One unit: MtCO₂e
1850 Emission quantity in 1850
1851 Emission quantity in 1850
.. Emission quantity in 1851
2019 Emission quantity in 2019

Sector categories by data source:

We observe that sector catagories differ depending on data sources:

# get sectors from different data sources
sector_CAIT = ghg_emissions_wri %>% 
  filter(Data.source == "CAIT") %>% 
  distinct(Sector) %>% 
  select(Sector.CAIT = Sector) %>% 
  arrange(Sector.CAIT)

sector_PIK = ghg_emissions_wri %>% 
  # select PIK datasource
  filter(Data.source == "PIK") %>% 
  distinct(Sector) %>% 
  select(Sector.PIK = Sector) %>% 
  arrange(Sector.PIK)

sector_GCP = ghg_emissions_wri %>% 
  # select GCP datasource
  filter(Data.source == "GCP") %>% 
  distinct(Sector) %>% 
  select(Sector.GCP = Sector) %>% 
  arrange(Sector.GCP)

sector_UNFCCC_AI = ghg_emissions_wri %>% 
  # select UNFCCC_AI datasource
  filter(Data.source == "UNFCCC_AI") %>% 
  distinct(Sector) %>%  
  select(Sector.UNFCCC_AI = Sector) %>% 
  arrange(Sector.UNFCCC_AI)

sector_UNFCCC_NAI = ghg_emissions_wri %>% 
  # select UNFCCC_NAI datasource
  filter(Data.source == "UNFCCC_NAI") %>% 
  distinct(Sector) %>% 
  select(Sector.UNFCCC_NAI = Sector) %>% 
  arrange(Sector.UNFCCC_NAI)

# plot table
knitr::kable(list(sector_CAIT, sector_PIK, sector_GCP, sector_UNFCCC_AI, sector_UNFCCC_NAI)) %>% 
  kable_styling(bootstrap_options = c("striped", "hover"), full_width = F, font_size = 12) %>% 
  scroll_box(width = "100%", height = "200px")
Sector.CAIT
Agriculture
Building
Bunker Fuels
Electricity/Heat
Energy
Fugitive Emissions
Industrial Processes
Land-Use Change and Forestry
Manufacturing/Construction
Other Fuel Combustion
Total excluding LUCF
Total including LUCF
Transportation
Waste
Sector.PIK
Agriculture
Energy
Industrial Processes and Product Use
Other
Total excluding LULUCF
Waste
Sector.GCP
Bunkers
Cement
Coal
Gas
Gas flaring
Oil
Total fossil fuels and cement
Sector.UNFCCC_AI
Agriculture
Energy
Industrial Processes and Product Use
Land Use, Land-Use Change and Forestry
Other
Total GHG emissions with LULUCF
Total GHG emissions without LULUCF
Waste
Sector.UNFCCC_NAI
Agriculture
Energy
Industrial Processes
Land-Use Change and Forestry
Other
Solvent and Other Product Use
Total GHG emissions excluding LULUCF/LUCF
Total GHG emissions including LULUCF/LUCF
Waste

Gas categories by data source

We observe that gases catagories differ depending on data sources:

# get gas from different data sources
gas_CAIT = ghg_emissions_wri %>% 
  filter(Data.source == "CAIT") %>% 
  distinct(Gas) %>% 
  select(Gas.CAIT = Gas) %>% 
  arrange(Gas.CAIT)

gas_PIK = ghg_emissions_wri %>% 
  # select PIK datasource
  filter(Data.source == "PIK") %>% 
  distinct(Gas) %>% 
  select(Gas.PIK = Gas) %>% 
  arrange(Gas.PIK)

gas_GCP = ghg_emissions_wri %>% 
  # select GCP datasource
  filter(Data.source == "GCP") %>% 
  distinct(Gas) %>% 
  select(Gas.GCP = Gas) %>% 
  arrange(Gas.GCP)

gas_UNFCCC_AI = ghg_emissions_wri %>% 
  # select UNFCCC_AI datasource
  filter(Data.source == "UNFCCC_AI") %>% 
  distinct(Gas) %>%  
  select(Gas.UNFCCC_AI = Gas) %>% 
  arrange(Gas.UNFCCC_AI)

gas_UNFCCC_NAI = ghg_emissions_wri %>% 
  # select UNFCCC_NAI datasource
  filter(Data.source == "UNFCCC_NAI") %>% 
  distinct(Gas) %>% 
  select(Gas.UNFCCC_NAI = Gas) %>% 
  arrange(Gas.UNFCCC_NAI)

# plot table
knitr::kable(list(gas_CAIT, gas_PIK, gas_GCP, gas_UNFCCC_AI, gas_UNFCCC_NAI)) %>% 
  kable_styling(bootstrap_options = c("striped", "hover"), full_width = F, font_size = 12) %>% 
  scroll_box(width = "100%", height = "200px")
Gas.CAIT
All GHG
CH4
CO2
F-Gas
N2O
Gas.PIK
CH4
CO2
F-Gas
KYOTOGHG
N2O
Gas.GCP
CO2
Gas.UNFCCC_AI
Aggregate F-gases
Aggregate GHGs
CH4
CO2
N2O
Gas.UNFCCC_NAI
Aggregate F-gases
Aggregate GHGs
CH4
CO2
N2O

Considered countries by data source

The number of considered countries is not the same depending on the data sources as shown in the table below:

ghg_emissions_wri %>% 
  group_by(Data.source) %>% 
  summarise(Nb.Country=length(unique(Country))) %>% 
  kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover"), full_width = F, font_size = 13)
Data.source Nb.Country
CAIT 195
GCP 196
PIK 216
UNFCCC_AI 45
UNFCCC_NAI 148

  • CAIT data source contains data for 193 distinct countries (all countries that are member states of the United Nations) with aggregated data on world scale (World) and European Union (European Union (27))

  • GCP data source contains data for the 193 countries members states of the United Nations plus the state of Palestine and aggregated data on world scale (World) and European Union (European Union (27))

  • PIK data source contains data for the 193 countries members states of the United Nations in addition to aggregated data on groups of countries such as: Umbrella Group, Least Developed Countries, Non-Annex-I Parties to the Convention, Annex-I Parties to the Convention…

  • UNFCCC Annex I data source contains data for 43 countries members of the Annex I convention with aggregated data on belonging parties (Annex-I Parties to the Convention) and European Union scale (European Union (27)).

  • UNFCCC Non-Annex I data source contains data for 148 countries that are parts of the non-Annex I convention.

4.1.2.1 WRI-CAIT Data description

  • Description:

CAIT Historic allow for easy access, analysis and visualization of the latest available international greenhouse gas emissions data. It includes information for 191 countries and the European Union, 50 U.S. states, 6 gases, multiple economic sectors, and 160 years - carbon dioxide emissions for 1850-2014 and multi-sector greenhouse gas emission for 1990-2014.

More description is available here

  • License and reuse:

All CAIT data carries a Creative Commons Attribution-NonCommercial 4.0 International license. This means CAIT data and analysis can be used in non-commercial applications, provided clear attribution to WRI/CAIT is given. Additionally to citing CAIT it is recommended consider citing the data sources that CAIT is using.

CAIT 2.0 UNFCCC data derives directly from United Nations Framework Convention on Climate Change (UNFCCC) Secretariat. Additionally to citing CAIT 2.0 please consider citing UNFCCC data source that CAIT 2.0 is using: United Nations Framework Convention on Climate Change (UNFCCC) Secretariat. 2013. “Time Series – Annex I.” Bonn: UNFCCC.

# data processing

ghg_emissions_wri_CAIT = ghg_emissions_wri %>% 
  # select all world data & all gases data & total sector
  filter(Data.source == "CAIT",
         Country == "World", 
         Gas == "All GHG",
         Sector == "Total including LUCF") %>% 
  # pivot data
  pivot_longer(
    cols = starts_with("X"), 
    names_to = "year",
    names_prefix = "X",
    values_to = "value") %>% 
  mutate_at("year" , as.numeric) %>% 
  arrange(year)

# plot table
ghg_emissions_wri_CAIT %>% 
  kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover"), full_width = F, font_size = 13) %>% 
  scroll_box(width = "100%", height = "200px")
Country Data.source Sector Gas Unit year value
World CAIT Total including LUCF All GHG MtCO2e 1850 N/A
World CAIT Total including LUCF All GHG MtCO2e 1851 N/A
World CAIT Total including LUCF All GHG MtCO2e 1852 N/A
World CAIT Total including LUCF All GHG MtCO2e 1853 N/A
World CAIT Total including LUCF All GHG MtCO2e 1854 N/A
World CAIT Total including LUCF All GHG MtCO2e 1855 N/A
World CAIT Total including LUCF All GHG MtCO2e 1856 N/A
World CAIT Total including LUCF All GHG MtCO2e 1857 N/A
World CAIT Total including LUCF All GHG MtCO2e 1858 N/A
World CAIT Total including LUCF All GHG MtCO2e 1859 N/A
World CAIT Total including LUCF All GHG MtCO2e 1860 N/A
World CAIT Total including LUCF All GHG MtCO2e 1861 N/A
World CAIT Total including LUCF All GHG MtCO2e 1862 N/A
World CAIT Total including LUCF All GHG MtCO2e 1863 N/A
World CAIT Total including LUCF All GHG MtCO2e 1864 N/A
World CAIT Total including LUCF All GHG MtCO2e 1865 N/A
World CAIT Total including LUCF All GHG MtCO2e 1866 N/A
World CAIT Total including LUCF All GHG MtCO2e 1867 N/A
World CAIT Total including LUCF All GHG MtCO2e 1868 N/A
World CAIT Total including LUCF All GHG MtCO2e 1869 N/A
World CAIT Total including LUCF All GHG MtCO2e 1870 N/A
World CAIT Total including LUCF All GHG MtCO2e 1871 N/A
World CAIT Total including LUCF All GHG MtCO2e 1872 N/A
World CAIT Total including LUCF All GHG MtCO2e 1873 N/A
World CAIT Total including LUCF All GHG MtCO2e 1874 N/A
World CAIT Total including LUCF All GHG MtCO2e 1875 N/A
World CAIT Total including LUCF All GHG MtCO2e 1876 N/A
World CAIT Total including LUCF All GHG MtCO2e 1877 N/A
World CAIT Total including LUCF All GHG MtCO2e 1878 N/A
World CAIT Total including LUCF All GHG MtCO2e 1879 N/A
World CAIT Total including LUCF All GHG MtCO2e 1880 N/A
World CAIT Total including LUCF All GHG MtCO2e 1881 N/A
World CAIT Total including LUCF All GHG MtCO2e 1882 N/A
World CAIT Total including LUCF All GHG MtCO2e 1883 N/A
World CAIT Total including LUCF All GHG MtCO2e 1884 N/A
World CAIT Total including LUCF All GHG MtCO2e 1885 N/A
World CAIT Total including LUCF All GHG MtCO2e 1886 N/A
World CAIT Total including LUCF All GHG MtCO2e 1887 N/A
World CAIT Total including LUCF All GHG MtCO2e 1888 N/A
World CAIT Total including LUCF All GHG MtCO2e 1889 N/A
World CAIT Total including LUCF All GHG MtCO2e 1890 N/A
World CAIT Total including LUCF All GHG MtCO2e 1891 N/A
World CAIT Total including LUCF All GHG MtCO2e 1892 N/A
World CAIT Total including LUCF All GHG MtCO2e 1893 N/A
World CAIT Total including LUCF All GHG MtCO2e 1894 N/A
World CAIT Total including LUCF All GHG MtCO2e 1895 N/A
World CAIT Total including LUCF All GHG MtCO2e 1896 N/A
World CAIT Total including LUCF All GHG MtCO2e 1897 N/A
World CAIT Total including LUCF All GHG MtCO2e 1898 N/A
World CAIT Total including LUCF All GHG MtCO2e 1899 N/A
World CAIT Total including LUCF All GHG MtCO2e 1900 N/A
World CAIT Total including LUCF All GHG MtCO2e 1901 N/A
World CAIT Total including LUCF All GHG MtCO2e 1902 N/A
World CAIT Total including LUCF All GHG MtCO2e 1903 N/A
World CAIT Total including LUCF All GHG MtCO2e 1904 N/A
World CAIT Total including LUCF All GHG MtCO2e 1905 N/A
World CAIT Total including LUCF All GHG MtCO2e 1906 N/A
World CAIT Total including LUCF All GHG MtCO2e 1907 N/A
World CAIT Total including LUCF All GHG MtCO2e 1908 N/A
World CAIT Total including LUCF All GHG MtCO2e 1909 N/A
World CAIT Total including LUCF All GHG MtCO2e 1910 N/A
World CAIT Total including LUCF All GHG MtCO2e 1911 N/A
World CAIT Total including LUCF All GHG MtCO2e 1912 N/A
World CAIT Total including LUCF All GHG MtCO2e 1913 N/A
World CAIT Total including LUCF All GHG MtCO2e 1914 N/A
World CAIT Total including LUCF All GHG MtCO2e 1915 N/A
World CAIT Total including LUCF All GHG MtCO2e 1916 N/A
World CAIT Total including LUCF All GHG MtCO2e 1917 N/A
World CAIT Total including LUCF All GHG MtCO2e 1918 N/A
World CAIT Total including LUCF All GHG MtCO2e 1919 N/A
World CAIT Total including LUCF All GHG MtCO2e 1920 N/A
World CAIT Total including LUCF All GHG MtCO2e 1921 N/A
World CAIT Total including LUCF All GHG MtCO2e 1922 N/A
World CAIT Total including LUCF All GHG MtCO2e 1923 N/A
World CAIT Total including LUCF All GHG MtCO2e 1924 N/A
World CAIT Total including LUCF All GHG MtCO2e 1925 N/A
World CAIT Total including LUCF All GHG MtCO2e 1926 N/A
World CAIT Total including LUCF All GHG MtCO2e 1927 N/A
World CAIT Total including LUCF All GHG MtCO2e 1928 N/A
World CAIT Total including LUCF All GHG MtCO2e 1929 N/A
World CAIT Total including LUCF All GHG MtCO2e 1930 N/A
World CAIT Total including LUCF All GHG MtCO2e 1931 N/A
World CAIT Total including LUCF All GHG MtCO2e 1932 N/A
World CAIT Total including LUCF All GHG MtCO2e 1933 N/A
World CAIT Total including LUCF All GHG MtCO2e 1934 N/A
World CAIT Total including LUCF All GHG MtCO2e 1935 N/A
World CAIT Total including LUCF All GHG MtCO2e 1936 N/A
World CAIT Total including LUCF All GHG MtCO2e 1937 N/A
World CAIT Total including LUCF All GHG MtCO2e 1938 N/A
World CAIT Total including LUCF All GHG MtCO2e 1939 N/A
World CAIT Total including LUCF All GHG MtCO2e 1940 N/A
World CAIT Total including LUCF All GHG MtCO2e 1941 N/A
World CAIT Total including LUCF All GHG MtCO2e 1942 N/A
World CAIT Total including LUCF All GHG MtCO2e 1943 N/A
World CAIT Total including LUCF All GHG MtCO2e 1944 N/A
World CAIT Total including LUCF All GHG MtCO2e 1945 N/A
World CAIT Total including LUCF All GHG MtCO2e 1946 N/A
World CAIT Total including LUCF All GHG MtCO2e 1947 N/A
World CAIT Total including LUCF All GHG MtCO2e 1948 N/A
World CAIT Total including LUCF All GHG MtCO2e 1949 N/A
World CAIT Total including LUCF All GHG MtCO2e 1950 N/A
World CAIT Total including LUCF All GHG MtCO2e 1951 N/A
World CAIT Total including LUCF All GHG MtCO2e 1952 N/A
World CAIT Total including LUCF All GHG MtCO2e 1953 N/A
World CAIT Total including LUCF All GHG MtCO2e 1954 N/A
World CAIT Total including LUCF All GHG MtCO2e 1955 N/A
World CAIT Total including LUCF All GHG MtCO2e 1956 N/A
World CAIT Total including LUCF All GHG MtCO2e 1957 N/A
World CAIT Total including LUCF All GHG MtCO2e 1958 N/A
World CAIT Total including LUCF All GHG MtCO2e 1959 N/A
World CAIT Total including LUCF All GHG MtCO2e 1960 N/A
World CAIT Total including LUCF All GHG MtCO2e 1961 N/A
World CAIT Total including LUCF All GHG MtCO2e 1962 N/A
World CAIT Total including LUCF All GHG MtCO2e 1963 N/A
World CAIT Total including LUCF All GHG MtCO2e 1964 N/A
World CAIT Total including LUCF All GHG MtCO2e 1965 N/A
World CAIT Total including LUCF All GHG MtCO2e 1966 N/A
World CAIT Total including LUCF All GHG MtCO2e 1967 N/A
World CAIT Total including LUCF All GHG MtCO2e 1968 N/A
World CAIT Total including LUCF All GHG MtCO2e 1969 N/A
World CAIT Total including LUCF All GHG MtCO2e 1970 N/A
World CAIT Total including LUCF All GHG MtCO2e 1971 N/A
World CAIT Total including LUCF All GHG MtCO2e 1972 N/A
World CAIT Total including LUCF All GHG MtCO2e 1973 N/A
World CAIT Total including LUCF All GHG MtCO2e 1974 N/A
World CAIT Total including LUCF All GHG MtCO2e 1975 N/A
World CAIT Total including LUCF All GHG MtCO2e 1976 N/A
World CAIT Total including LUCF All GHG MtCO2e 1977 N/A
World CAIT Total including LUCF All GHG MtCO2e 1978 N/A
World CAIT Total including LUCF All GHG MtCO2e 1979 N/A
World CAIT Total including LUCF All GHG MtCO2e 1980 N/A
World CAIT Total including LUCF All GHG MtCO2e 1981 N/A
World CAIT Total including LUCF All GHG MtCO2e 1982 N/A
World CAIT Total including LUCF All GHG MtCO2e 1983 N/A
World CAIT Total including LUCF All GHG MtCO2e 1984 N/A
World CAIT Total including LUCF All GHG MtCO2e 1985 N/A
World CAIT Total including LUCF All GHG MtCO2e 1986 N/A
World CAIT Total including LUCF All GHG MtCO2e 1987 N/A
World CAIT Total including LUCF All GHG MtCO2e 1988 N/A
World CAIT Total including LUCF All GHG MtCO2e 1989 N/A
World CAIT Total including LUCF All GHG MtCO2e 1990 34964.58
World CAIT Total including LUCF All GHG MtCO2e 1991 35125.92
World CAIT Total including LUCF All GHG MtCO2e 1992 34982.15
World CAIT Total including LUCF All GHG MtCO2e 1993 35080.3
World CAIT Total including LUCF All GHG MtCO2e 1994 35283.88
World CAIT Total including LUCF All GHG MtCO2e 1995 36004.23
World CAIT Total including LUCF All GHG MtCO2e 1996 36022.1
World CAIT Total including LUCF All GHG MtCO2e 1997 37338.36
World CAIT Total including LUCF All GHG MtCO2e 1998 36981.63
World CAIT Total including LUCF All GHG MtCO2e 1999 36817.13
World CAIT Total including LUCF All GHG MtCO2e 2000 37438.04
World CAIT Total including LUCF All GHG MtCO2e 2001 38396.69
World CAIT Total including LUCF All GHG MtCO2e 2002 39855.92
World CAIT Total including LUCF All GHG MtCO2e 2003 40703.74
World CAIT Total including LUCF All GHG MtCO2e 2004 42477.66
World CAIT Total including LUCF All GHG MtCO2e 2005 43360.31
World CAIT Total including LUCF All GHG MtCO2e 2006 43739.49
World CAIT Total including LUCF All GHG MtCO2e 2007 44590.03
World CAIT Total including LUCF All GHG MtCO2e 2008 44953.73
World CAIT Total including LUCF All GHG MtCO2e 2009 44907.04
World CAIT Total including LUCF All GHG MtCO2e 2010 46637.83
World CAIT Total including LUCF All GHG MtCO2e 2011 47915.71
World CAIT Total including LUCF All GHG MtCO2e 2012 48477.53
World CAIT Total including LUCF All GHG MtCO2e 2013 49037.46
World CAIT Total including LUCF All GHG MtCO2e 2014 49494.56
World CAIT Total including LUCF All GHG MtCO2e 2015 49828.88
World CAIT Total including LUCF All GHG MtCO2e 2016 49312.19
World CAIT Total including LUCF All GHG MtCO2e 2017 49947.42
World CAIT Total including LUCF All GHG MtCO2e 2018 N/A
World CAIT Total including LUCF All GHG MtCO2e 2019 N/A

4.1.2.2 WRI-CAIT Data mapping

OGS.MAP.WRI.CAIT = function(wri_data, start_date, end_date, geoscale, datasource.filter, geoname.filter, gas.filter, sector.filter){
  wri_data_OGS = wri_data %>% 
    filter(Data.source == datasource.filter,
           Country == geoname.filter) %>% 
    # recode sectors and gas values
    mutate(sector = fct_collapse(Sector, "All" = "Total including LUCF"),
           gas = fct_collapse(Gas, "All" = "All GHG")) %>% 
    # filter gas and sector
    filter(sector == sector.filter,
           gas == gas.filter) %>% 
    # pivot data
    pivot_longer(
      cols = starts_with("X"), 
      names_to = "year",
      names_prefix = "X",
      values_to = "value") %>% 
    mutate_at("year" , as.numeric) %>% 
    arrange(year) %>% 
    add_column(data.provider = "WRI.CAIT",
               geo.scale = geoscale,
               geo.code.iso3c = NA,
               geo.code.iso2c = NA,
               unit = "MtCO₂e") %>% 
    rename(data.source = Data.source,
           geo.name = Country,
           value = value) %>% 
    select(data.source, data.provider, geo.scale, geo.code.iso2c, geo.code.iso3c, geo.name,
           year, sector, gas, value) %>% 
    filter(year >= start_date & year <= end_date) %>% 
    mutate_at("value" , as.numeric) 
  
  return(wri_data_OGS)
}


wri_data_OGS = OGS.MAP.WRI.CAIT(wri_data = ghg_emissions_wri,
                                datasource.filter = "CAIT",
                                geoname.filter = "World",
                                gas.filter = "All",
                                sector.filter = "All",
                                geoscale = "World",
                                start_date = 1990,
                                end_date = 2016)

# plot timeserie
wri_data_OGS %>% 
  # filter(year >= 1990 & year < 2017) %>% 
  plot_ly() %>% 
  add_trace(y = ~value, 
            x = ~year, 
            type = 'scatter',
            mode = 'lines+markers',
            orientation = "v",
            hoverinfo = 'text',
            text = ~paste('</br> Year: ', year,
                          '</br> Value: ', value,
                          '</br> Gas: ', gas,
                          '</br> Sector: ', sector,
                          '</br> Source: ', data.provider)) %>% 
  layout(title = "World GHG emissions (source: WRI - CAIT)",
         yaxis = list(title = "GHG emissions"), 
         xaxis = list(title = "Years"))

4.1.2.3 WRI - GCP

4.1.2.4 WRI - UNFCCC

4.1.2.5 WRI - PIK

4.1.3 Our world in data

4.1.3.1 Data description

# read co2 data
ghg_emissions_owid= read.csv("https://raw.githubusercontent.com/owid/co2-data/master/owid-co2-data.csv", 
                             encoding = "UTF-8")
# plot table
ghg_emissions_owid %>% 
  filter(country == "World") %>% 
  kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover"), full_width = F, font_size = 13) %>% 
  scroll_box(width = "100%", height = "200px")
iso_code country year co2 co2_growth_prct co2_growth_abs consumption_co2 trade_co2 trade_co2_share co2_per_capita consumption_co2_per_capita share_global_co2 cumulative_co2 share_global_cumulative_co2 co2_per_gdp consumption_co2_per_gdp co2_per_unit_energy cement_co2 coal_co2 flaring_co2 gas_co2 oil_co2 other_industry_co2 cement_co2_per_capita coal_co2_per_capita flaring_co2_per_capita gas_co2_per_capita oil_co2_per_capita other_co2_per_capita share_global_coal_co2 share_global_oil_co2 share_global_gas_co2 share_global_flaring_co2 share_global_cement_co2 cumulative_coal_co2 cumulative_oil_co2 cumulative_gas_co2 cumulative_flaring_co2 cumulative_cement_co2 share_global_cumulative_coal_co2 share_global_cumulative_oil_co2 share_global_cumulative_gas_co2 share_global_cumulative_flaring_co2 share_global_cumulative_cement_co2 total_ghg ghg_per_capita methane methane_per_capita nitrous_oxide nitrous_oxide_per_capita primary_energy_consumption energy_per_capita energy_per_gdp population gdp
OWID_WRL World 1750 9.351 NA NA NA NA NA 0.012 NA 100 9.351 100 NA NA NA NA 9.351 NA NA NA NA NA 0.012 NA NA NA NA 100 NA NA NA NA 9.351 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA 811562112 NA
OWID_WRL World 1751 9.351 NA NA NA NA NA NA NA 100 18.701 100 NA NA NA NA 9.351 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 18.701 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1752 9.354 0.039 0.004 NA NA NA NA NA 100 28.055 100 NA NA NA NA 9.354 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 28.055 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1753 9.354 NA NA NA NA NA NA NA 100 37.409 100 NA NA NA NA 9.354 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 37.409 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1754 9.358 0.039 0.004 NA NA NA NA NA 100 46.767 100 NA NA NA NA 9.358 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 46.767 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1755 9.362 0.039 0.004 NA NA NA NA NA 100 56.129 100 NA NA NA NA 9.362 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 56.129 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1756 10.006 6.888 0.645 NA NA NA NA NA 100 66.135 100 NA NA NA NA 10.006 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 66.135 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1757 10.010 0.037 0.004 NA NA NA NA NA 100 76.145 100 NA NA NA NA 10.010 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 76.145 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1758 10.014 0.037 0.004 NA NA NA NA NA 100 86.159 100 NA NA NA NA 10.014 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 86.159 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1759 10.017 0.037 0.004 NA NA NA NA NA 100 96.176 100 NA NA NA NA 10.017 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 96.176 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1760 10.017 NA NA NA NA NA NA NA 100 106.194 100 NA NA NA NA 10.017 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 106.194 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1761 10.974 9.546 0.956 NA NA NA NA NA 100 117.167 100 NA NA NA NA 10.974 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 117.167 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1762 10.977 0.033 0.004 NA NA NA NA NA 100 128.145 100 NA NA NA NA 10.977 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 128.145 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1763 10.981 0.033 0.004 NA NA NA NA NA 100 139.126 100 NA NA NA NA 10.981 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 139.126 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1764 10.985 0.033 0.004 NA NA NA NA NA 100 150.110 100 NA NA NA NA 10.985 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 150.110 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1765 10.988 0.033 0.004 NA NA NA NA NA 100 161.099 100 NA NA NA NA 10.988 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 161.099 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1766 12.260 11.571 1.271 NA NA NA NA NA 100 173.358 100 NA NA NA NA 12.260 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 173.358 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1767 12.263 0.030 0.004 NA NA NA NA NA 100 185.622 100 NA NA NA NA 12.263 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 185.622 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1768 12.267 0.030 0.004 NA NA NA NA NA 100 197.889 100 NA NA NA NA 12.267 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 197.889 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1769 12.271 0.030 0.004 NA NA NA NA NA 100 210.160 100 NA NA NA NA 12.271 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 210.160 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1770 12.274 0.030 0.004 NA NA NA NA NA 100 222.434 100 NA NA NA NA 12.274 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 222.434 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1771 13.612 10.896 1.337 NA NA NA NA NA 100 236.046 100 NA NA NA NA 13.612 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 236.046 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1772 13.615 0.027 0.004 NA NA NA NA NA 100 249.661 100 NA NA NA NA 13.615 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 249.661 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1773 13.619 0.027 0.004 NA NA NA NA NA 100 263.280 100 NA NA NA NA 13.619 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 263.280 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1774 13.623 0.027 0.004 NA NA NA NA NA 100 276.903 100 NA NA NA NA 13.623 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 276.903 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1775 13.626 0.027 0.004 NA NA NA NA NA 100 290.530 100 NA NA NA NA 13.626 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 290.530 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1776 15.037 10.352 1.411 NA NA NA NA NA 100 305.567 100 NA NA NA NA 15.037 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 305.567 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1777 15.041 0.024 0.004 NA NA NA NA NA 100 320.607 100 NA NA NA NA 15.041 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 320.607 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1778 15.044 0.024 0.004 NA NA NA NA NA 100 335.652 100 NA NA NA NA 15.044 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 335.652 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1779 15.048 0.024 0.004 NA NA NA NA NA 100 350.700 100 NA NA NA NA 15.048 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 350.700 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1780 15.055 0.049 0.007 NA NA NA NA NA 100 365.755 100 NA NA NA NA 15.055 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 365.755 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1781 16.843 11.876 1.788 NA NA NA NA NA 100 382.599 100 NA NA NA NA 16.843 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 382.599 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1782 16.847 0.022 0.004 NA NA NA NA NA 100 399.446 100 NA NA NA NA 16.847 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 399.446 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1783 16.854 0.043 0.007 NA NA NA NA NA 100 416.300 100 NA NA NA NA 16.854 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 416.300 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1784 16.858 0.022 0.004 NA NA NA NA NA 100 433.158 100 NA NA NA NA 16.858 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 433.158 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1785 16.869 0.065 0.011 NA NA NA NA NA 100 450.027 100 NA NA NA NA 16.869 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 450.027 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1786 19.152 13.532 2.283 NA NA NA NA NA 100 469.179 100 NA NA NA NA 19.152 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 469.179 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1787 19.159 0.038 0.007 NA NA NA NA NA 100 488.338 100 NA NA NA NA 19.159 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 488.338 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1788 19.163 0.019 0.004 NA NA NA NA NA 100 507.501 100 NA NA NA NA 19.163 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 507.501 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1789 19.170 0.038 0.007 NA NA NA NA NA 100 526.671 100 NA NA NA NA 19.170 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 526.671 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1790 19.177 0.038 0.007 NA NA NA NA NA 100 545.848 100 NA NA NA NA 19.177 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 545.848 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1791 21.420 11.693 2.242 NA NA NA NA NA 100 567.268 100 NA NA NA NA 21.420 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 567.268 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1792 21.896 2.224 0.476 NA NA NA NA NA 100 589.164 100 NA NA NA NA 21.896 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 589.164 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1793 21.914 0.084 0.018 NA NA NA NA NA 100 611.078 100 NA NA NA NA 21.914 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 611.078 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1794 21.881 -0.150 -0.033 NA NA NA NA NA 100 632.960 100 NA NA NA NA 21.881 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 632.960 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1795 21.892 0.050 0.011 NA NA NA NA NA 100 654.852 100 NA NA NA NA 21.892 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 654.852 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1796 22.951 4.837 1.059 NA NA NA NA NA 100 677.803 100 NA NA NA NA 22.951 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 677.803 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1797 24.094 4.981 1.143 NA NA NA NA NA 100 701.898 100 NA NA NA NA 24.094 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 701.898 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1798 25.095 4.151 1.000 NA NA NA NA NA 100 726.993 100 NA NA NA NA 25.095 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 726.993 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1799 26.428 5.315 1.334 NA NA NA NA NA 100 753.421 100 NA NA NA NA 26.428 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 753.421 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1800 28.092 6.294 1.663 NA NA NA 0.028 NA 100 781.513 100 NA NA NA NA 28.092 NA NA NA NA NA 0.028 NA NA NA NA 100 NA NA NA NA 781.513 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA 989818304 NA
OWID_WRL World 1801 27.960 -0.470 -0.132 NA NA NA NA NA 100 809.473 100 NA NA NA NA 27.960 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 809.473 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1802 36.783 31.555 8.823 NA NA NA NA NA 100 846.256 100 NA NA NA NA 36.783 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 846.256 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1803 31.488 -14.394 -5.294 NA NA NA NA NA 100 877.744 100 NA NA NA NA 31.488 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 877.744 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1804 34.310 8.960 2.821 NA NA NA NA NA 100 912.054 100 NA NA NA NA 34.310 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 912.054 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1805 33.419 -2.595 -0.890 NA NA NA NA NA 100 945.473 100 NA NA NA NA 33.419 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 945.473 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1806 35.046 4.868 1.627 NA NA NA NA NA 100 980.519 100 NA NA NA NA 35.046 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 980.519 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1807 36.874 5.217 1.828 NA NA NA NA NA 100 1017.394 100 NA NA NA NA 36.874 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1017.394 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1808 35.064 -4.909 -1.810 NA NA NA NA NA 100 1052.458 100 NA NA NA NA 35.064 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1052.458 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1809 35.090 0.073 0.026 NA NA NA NA NA 100 1087.548 100 NA NA NA NA 35.090 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1087.548 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1810 37.380 6.526 2.290 NA NA NA NA NA 100 1124.929 100 NA NA NA NA 37.380 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1124.929 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1811 39.582 5.891 2.202 NA NA NA NA NA 100 1164.511 100 NA NA NA NA 39.582 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1164.511 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1812 41.007 3.601 1.425 NA NA NA NA NA 100 1205.518 100 NA NA NA NA 41.007 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1205.518 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1813 41.220 0.518 0.213 NA NA NA NA NA 100 1246.738 100 NA NA NA NA 41.220 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1246.738 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1814 42.129 2.204 0.909 NA NA NA NA NA 100 1288.867 100 NA NA NA NA 42.129 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1288.867 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1815 43.488 3.227 1.359 NA NA NA NA NA 100 1332.355 100 NA NA NA NA 43.488 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1332.355 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1816 47.665 9.605 4.177 NA NA NA NA NA 100 1380.020 100 NA NA NA NA 47.665 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1380.020 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1817 49.431 3.705 1.766 NA NA NA NA NA 100 1429.451 100 NA NA NA NA 49.431 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1429.451 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1818 49.644 0.430 0.213 NA NA NA NA NA 100 1479.095 100 NA NA NA NA 49.644 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1479.095 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1819 49.948 0.613 0.304 NA NA NA NA NA 100 1529.042 100 NA NA NA NA 49.948 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1529.042 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1820 50.688 1.482 0.740 NA NA NA NA NA 100 1579.730 100 NA NA NA NA 50.688 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1579.730 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1821 51.435 1.475 0.747 NA NA NA NA NA 100 1631.165 100 NA NA NA NA 51.435 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1631.165 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1822 53.465 3.946 2.030 NA NA NA NA NA 100 1684.630 100 NA NA NA NA 53.465 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1684.630 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1823 56.550 5.770 3.085 NA NA NA NA NA 100 1741.180 100 NA NA NA NA 56.550 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1741.180 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1824 58.525 3.492 1.975 NA NA NA NA NA 100 1799.706 100 NA NA NA NA 58.525 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1799.706 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1825 60.756 3.813 2.231 NA NA NA NA NA 100 1860.462 100 NA NA NA NA 60.756 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1860.462 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1826 61.420 1.092 0.663 NA NA NA NA NA 100 1921.882 100 NA NA NA NA 61.420 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1921.882 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1827 65.915 7.320 4.496 NA NA NA NA NA 100 1987.797 100 NA NA NA NA 65.915 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 1987.797 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1828 66.637 1.095 0.722 NA NA NA NA NA 100 2054.434 100 NA NA NA NA 66.637 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 2054.434 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1829 66.395 -0.363 -0.242 NA NA NA NA NA 100 2120.829 100 NA NA NA NA 66.395 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 2120.829 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1830 89.123 34.231 22.728 NA NA NA NA NA 100 2209.953 100 NA NA NA NA 89.123 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 2209.953 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1831 84.528 -5.155 -4.595 NA NA NA NA NA 100 2294.481 100 NA NA NA NA 84.528 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 2294.481 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1832 85.111 0.689 0.583 NA NA NA NA NA 100 2379.592 100 NA NA NA NA 85.111 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 2379.592 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1833 86.807 1.993 1.696 NA NA NA NA NA 100 2466.400 100 NA NA NA NA 86.807 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 2466.400 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1834 88.486 1.933 1.678 NA NA NA NA NA 100 2554.885 100 NA NA NA NA 88.486 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 2554.885 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1835 90.446 2.215 1.960 NA NA NA NA NA 100 2645.331 100 NA NA NA NA 90.446 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 2645.331 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1836 104.776 15.844 14.330 NA NA NA NA NA 100 2750.107 100 NA NA NA NA 104.776 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 2750.107 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1837 104.691 -0.080 -0.084 NA NA NA NA NA 100 2854.798 100 NA NA NA NA 104.691 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 2854.798 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1838 108.044 3.202 3.353 NA NA NA NA NA 100 2962.842 100 NA NA NA NA 108.044 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 2962.842 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1839 111.613 3.303 3.569 NA NA NA NA NA 100 3074.455 100 NA NA NA NA 111.613 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 3074.455 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1840 118.930 6.556 7.317 NA NA NA NA NA 100 3193.385 100 NA NA NA NA 118.930 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 3193.385 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1841 122.619 3.102 3.690 NA NA NA NA NA 100 3316.004 100 NA NA NA NA 122.619 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 3316.004 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1842 129.504 5.615 6.885 NA NA NA NA NA 100 3445.508 100 NA NA NA NA 129.504 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 3445.508 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1843 132.853 2.586 3.349 NA NA NA NA NA 100 3578.361 100 NA NA NA NA 132.853 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 3578.361 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1844 141.423 6.451 8.570 NA NA NA NA NA 100 3719.784 100 NA NA NA NA 141.423 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 3719.784 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1845 155.211 9.749 13.788 NA NA NA NA NA 100 3874.995 100 NA NA NA NA 155.211 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 3874.995 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1846 157.794 1.664 2.583 NA NA NA NA NA 100 4032.789 100 NA NA NA NA 157.794 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 4032.789 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1847 172.402 9.258 14.608 NA NA NA NA NA 100 4205.191 100 NA NA NA NA 172.402 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 4205.191 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1848 173.816 0.820 1.414 NA NA NA NA NA 100 4379.008 100 NA NA NA NA 173.816 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 4379.008 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1849 183.511 5.578 9.695 NA NA NA NA NA 100 4562.519 100 NA NA NA NA 183.511 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 4562.519 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1850 196.896 7.294 13.385 NA NA NA 0.156 NA 100 4759.415 100 NA NA NA NA 196.896 NA NA NA NA NA 0.156 NA NA NA NA 100 NA NA NA NA 4759.415 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA 1262682112 NA
OWID_WRL World 1851 198.805 0.970 1.909 NA NA NA NA NA 100 4958.220 100 NA NA NA NA 198.805 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 4958.220 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1852 207.551 4.399 8.746 NA NA NA NA NA 100 5165.771 100 NA NA NA NA 207.551 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 5165.771 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1853 217.209 4.653 9.658 NA NA NA NA NA 100 5382.980 100 NA NA NA NA 217.209 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 5382.980 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1854 255.139 17.462 37.930 NA NA NA NA NA 100 5638.119 100 NA NA NA NA 255.139 NA NA NA NA NA NA NA NA NA NA 100 NA NA NA NA 5638.119 NA NA NA NA 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1855 260.166 1.970 5.027 NA NA NA NA NA 100 5898.285 100 NA NA NA NA 260.129 NA NA 0.037 NA NA NA NA NA NA NA 100 100 NA NA NA 5898.249 0.037 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1856 277.292 6.583 17.126 NA NA NA NA NA 100 6175.577 100 NA NA NA NA 277.251 NA NA 0.040 NA NA NA NA NA NA NA 100 100 NA NA NA 6175.500 0.077 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1857 279.889 0.937 2.598 NA NA NA NA NA 100 6455.466 100 NA NA NA NA 279.838 NA NA 0.051 NA NA NA NA NA NA NA 100 100 NA NA NA 6455.338 0.128 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1858 284.172 1.530 4.283 NA NA NA NA NA 100 6739.638 100 NA NA NA NA 284.110 NA NA 0.062 NA NA NA NA NA NA NA 100 100 NA NA NA 6739.448 0.191 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1859 301.313 6.032 17.141 NA NA NA NA NA 100 7040.951 100 NA NA NA NA 301.258 NA NA 0.055 NA NA NA NA NA NA NA 100 100 NA NA NA 7040.705 0.245 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1860 330.642 9.734 29.330 NA NA NA NA NA 100 7371.593 100 NA NA NA NA 330.369 NA NA 0.274 NA NA NA NA NA NA NA 100 100 NA NA NA 7371.074 0.519 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1861 347.735 5.170 17.093 NA NA NA NA NA 100 7719.329 100 NA NA NA NA 346.794 NA NA 0.942 NA NA NA NA NA NA NA 100 100 NA NA NA 7717.868 1.461 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1862 354.058 1.818 6.322 NA NA NA NA NA 100 8073.387 100 NA NA NA NA 352.659 NA NA 1.399 NA NA NA NA NA NA NA 100 100 NA NA NA 8070.526 2.860 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1863 377.860 6.723 23.803 NA NA NA NA NA 100 8451.247 100 NA NA NA NA 376.566 NA NA 1.294 NA NA NA NA NA NA NA 100 100 NA NA NA 8447.093 4.154 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1864 407.091 7.736 29.231 NA NA NA NA NA 100 8858.338 100 NA NA NA NA 405.981 NA NA 1.111 NA NA NA NA NA NA NA 100 100 NA NA NA 8853.073 5.265 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1865 432.308 6.194 25.217 NA NA NA NA NA 100 9290.646 100 NA NA NA NA 430.987 NA NA 1.321 NA NA NA NA NA NA NA 100 100 NA NA NA 9284.061 6.585 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1866 445.971 3.160 13.663 NA NA NA NA NA 100 9736.617 100 NA NA NA NA 444.017 NA NA 1.954 NA NA NA NA NA NA NA 100 100 NA NA NA 9728.078 8.539 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1867 477.815 7.140 31.844 NA NA NA NA NA 100 10214.432 100 NA NA NA NA 475.828 NA NA 1.987 NA NA NA NA NA NA NA 100 100 NA NA NA 10203.906 10.526 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1868 490.752 2.708 12.938 NA NA NA NA NA 100 10705.185 100 NA NA NA NA 488.461 NA NA 2.291 NA NA NA NA NA NA NA 100 100 NA NA NA 10692.367 12.817 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1869 521.131 6.190 30.378 NA NA NA NA NA 100 11226.315 100 NA NA NA NA 518.513 NA NA 2.617 NA NA NA NA NA NA NA 100 100 NA NA NA 11210.881 15.435 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1870 532.537 2.189 11.406 NA NA NA NA NA 100 11758.852 100 0.416 NA NA NA 529.401 NA NA 3.136 NA NA NA NA NA NA NA 100 100 NA NA NA 11740.281 18.571 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA 1.28061e+12
OWID_WRL World 1871 566.143 6.311 33.606 NA NA NA NA NA 100 12324.995 100 NA NA NA NA 562.858 NA NA 3.285 NA NA NA NA NA NA NA 100 100 NA NA NA 12303.139 21.856 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1872 626.372 10.638 60.229 NA NA NA NA NA 100 12951.367 100 NA NA NA NA 622.670 NA NA 3.702 NA NA NA NA NA NA NA 100 100 NA NA NA 12925.809 25.558 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1873 665.419 6.234 39.047 NA NA NA NA NA 100 13616.786 100 NA NA NA NA 659.745 NA NA 5.674 NA NA NA NA NA NA NA 100 100 NA NA NA 13585.554 31.232 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1874 622.997 -6.375 -42.422 NA NA NA NA NA 100 14239.783 100 NA NA NA NA 616.748 NA NA 6.249 NA NA NA NA NA NA NA 100 100 NA NA NA 14202.302 37.481 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1875 675.799 8.475 52.802 NA NA NA NA NA 100 14915.582 100 NA NA NA NA 669.957 NA NA 5.843 NA NA NA NA NA NA NA 100 100 NA NA NA 14872.258 43.324 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1876 685.553 1.443 9.754 NA NA NA NA NA 100 15601.135 100 NA NA NA NA 679.007 NA NA 6.545 NA NA NA NA NA NA NA 100 100 NA NA NA 15551.266 49.869 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1877 699.099 1.976 13.546 NA NA NA NA NA 100 16300.233 100 NA NA NA NA 690.264 NA NA 8.835 NA NA NA NA NA NA NA 100 100 NA NA NA 16241.529 58.704 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1878 704.383 0.756 5.284 NA NA NA NA NA 100 17004.616 100 NA NA NA NA 694.328 NA NA 10.054 NA NA NA NA NA NA NA 100 100 NA NA NA 16935.858 68.758 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1879 754.870 7.168 50.488 NA NA NA NA NA 100 17759.486 100 NA NA NA NA 742.195 NA NA 12.675 NA NA NA NA NA NA NA 100 100 NA NA NA 17678.053 81.433 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1880 853.708 13.093 98.838 NA NA NA NA NA 100 18613.194 100 NA NA NA NA 838.326 NA NA 15.382 NA NA NA NA NA NA NA 100 100 NA NA NA 18516.379 96.815 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1881 882.408 3.362 28.700 NA NA NA NA NA 100 19495.602 100 NA NA NA NA 865.143 NA NA 17.265 NA NA NA NA NA NA NA 100 100 NA NA NA 19381.522 114.080 NA NA NA 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1882 931.925 5.612 49.517 NA NA NA NA NA 100 20427.528 100 NA NA NA NA 912.796 NA 0.165 18.964 NA NA NA NA NA NA NA 100 100 100 NA NA 20294.319 133.044 0.165 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1883 991.036 6.343 59.111 NA NA NA NA NA 100 21418.564 100 NA NA NA NA 974.126 NA 0.381 16.529 NA NA NA NA NA NA NA 100 100 100 NA NA 21268.445 149.573 0.546 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1884 1002.179 1.124 11.142 NA NA NA NA NA 100 22420.742 100 NA NA NA NA 982.645 NA 1.172 18.361 NA NA NA NA NA NA NA 100 100 100 NA NA 22251.090 167.934 1.718 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1885 1009.675 0.748 7.497 NA NA NA NA NA 100 23430.418 100 NA NA NA NA 986.953 NA 3.715 19.007 NA NA NA NA NA NA NA 100 100 100 NA NA 23238.043 186.941 5.434 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1886 1025.480 1.565 15.804 NA NA NA NA NA 100 24455.897 100 NA NA NA NA 995.930 NA 7.676 21.873 NA NA NA NA NA NA NA 100 100 100 NA NA 24233.973 208.815 13.110 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1887 1076.762 5.001 51.283 NA NA NA NA NA 100 25532.660 100 NA NA NA NA 1041.434 NA 11.787 23.541 NA NA NA NA NA NA NA 100 100 100 NA NA 25275.407 232.356 24.897 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1888 1192.277 10.728 115.515 NA NA NA NA NA 100 26724.937 100 NA NA NA NA 1150.859 NA 16.774 24.644 NA NA NA NA NA NA NA 100 100 100 NA NA 26426.266 257.000 41.671 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1889 1191.805 -0.040 -0.471 NA NA NA NA NA 100 27916.742 100 NA NA NA NA 1151.106 NA 12.227 28.473 NA NA NA NA NA NA NA 100 100 100 NA NA 27577.372 285.473 53.897 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1890 1298.465 8.949 106.659 NA NA NA NA NA 100 29215.207 100 0.593 NA NA NA 1252.048 NA 11.688 34.728 NA NA NA NA NA NA NA 100 100 100 NA NA 28829.420 320.201 65.585 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA 2.18872e+12
OWID_WRL World 1891 1358.881 4.653 60.416 NA NA NA NA NA 100 30574.088 100 NA NA NA NA 1309.013 NA 8.947 40.921 NA NA NA NA NA NA NA 100 100 100 NA NA 30138.433 361.122 74.533 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1892 1370.085 0.824 11.204 NA NA NA NA NA 100 31944.172 100 NA NA NA NA 1322.020 NA 7.775 40.289 NA NA NA NA NA NA NA 100 100 100 NA NA 31460.453 401.411 82.308 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1893 1353.676 -1.198 -16.408 NA NA NA NA NA 100 33297.849 100 NA NA NA NA 1303.732 NA 7.288 42.657 NA NA NA NA NA NA NA 100 100 100 NA NA 32764.185 444.068 89.596 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1894 1400.866 3.486 47.190 NA NA NA NA NA 100 34698.715 100 NA NA NA NA 1352.360 NA 6.698 41.808 NA NA NA NA NA NA NA 100 100 100 NA NA 34116.545 485.877 96.294 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1895 1485.283 6.026 84.417 NA NA NA NA NA 100 36183.998 100 NA NA NA NA 1429.571 NA 7.042 48.671 NA NA NA NA NA NA NA 100 100 100 NA NA 35546.115 534.547 103.336 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1896 1533.713 3.261 48.430 NA NA NA NA NA 100 37717.712 100 NA NA NA NA 1474.161 NA 6.848 52.704 NA NA NA NA NA NA NA 100 100 100 NA NA 37020.276 587.252 110.184 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1897 1606.313 4.734 72.600 NA NA NA NA NA 100 39324.025 100 NA NA NA NA 1543.341 NA 7.288 55.684 NA NA NA NA NA NA NA 100 100 100 NA NA 38563.618 642.936 117.471 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1898 1694.280 5.476 87.967 NA NA NA NA NA 100 41018.304 100 NA NA NA NA 1628.475 NA 8.460 57.345 NA NA NA NA NA NA NA 100 100 100 NA NA 40192.093 700.280 125.931 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1899 1850.909 9.245 156.629 NA NA NA NA NA 100 42869.213 100 NA NA NA NA 1779.779 NA 10.904 60.226 NA NA NA NA NA NA NA 100 100 100 NA NA 41971.871 760.506 136.836 NA NA 100 100 100 NA NA NA NA NA NA NA NA NA NA NA NA NA
OWID_WRL World 1900 1953.614 5.549 102.705 NA NA NA 1.184 NA 100 44822.827 100 NA NA NA 1.386 1873.155 NA 11.542 67.532 NA 0.001 1.135 NA 0.007 0.041 NA 100 100 100 NA 100 43845.026 828.038 148.377 NA 1.386 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1650000000 NA
OWID_WRL World 1901 2018.421 3.317 64.806 NA NA NA 1.216 NA 100 46841.248 100 NA NA NA 1.656 1928.919 NA 12.861 74.985 NA 0.001 1.162 NA 0.008 0.045 NA 100 100 100 NA 100 45773.945 903.023 161.238 NA 3.042 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1659947520 NA
OWID_WRL World 1902 2069.946 2.553 51.526 NA NA NA 1.239 NA 100 48911.194 100 NA NA NA 2.145 1973.072 NA 13.696 81.033 NA 0.001 1.181 NA 0.008 0.049 NA 100 100 100 NA 100 47747.017 984.056 174.934 NA 5.187 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1669996544 NA
OWID_WRL World 1903 2258.613 9.115 188.667 NA NA NA 1.344 NA 100 51169.808 100 NA NA NA 2.533 2155.776 NA 14.528 85.776 NA 0.002 1.283 NA 0.009 0.051 NA 100 100 100 NA 100 49902.794 1069.833 189.462 NA 7.720 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1680114944 NA
OWID_WRL World 1904 2282.759 1.069 24.146 NA NA NA 1.351 NA 100 53452.567 100 NA NA NA 2.732 2168.548 NA 15.165 96.315 NA 0.002 1.283 NA 0.009 0.057 NA 100 100 100 NA 100 52071.341 1166.148 204.627 NA 10.451 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1690269440 NA
OWID_WRL World 1905 2431.145 6.500 148.385 NA NA NA 1.430 NA 100 55883.712 100 NA NA NA 3.491 2313.287 NA 17.170 97.198 NA 0.002 1.360 NA 0.010 0.057 NA 100 100 100 NA 100 54384.628 1263.345 221.796 NA 13.942 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1700426240 NA
OWID_WRL World 1906 2554.215 5.062 123.071 NA NA NA 1.493 NA 100 58437.927 100 NA NA NA 4.470 2432.620 NA 19.027 98.099 NA 0.003 1.422 NA 0.011 0.057 NA 100 100 100 NA 100 56817.248 1361.444 240.823 NA 18.411 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1710550656 NA
OWID_WRL World 1907 2887.833 13.061 333.617 NA NA NA 1.678 NA 100 61325.760 100 NA NA NA 4.601 2743.719 NA 19.877 119.636 NA 0.003 1.595 NA 0.012 0.070 NA 100 100 100 NA 100 59560.967 1481.080 260.701 NA 23.012 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1720606976 NA
OWID_WRL World 1908 2779.288 -3.759 -108.545 NA NA NA 1.606 NA 100 64105.048 100 NA NA NA 4.795 2625.838 NA 19.676 128.979 NA 0.003 1.517 NA 0.011 0.075 NA 100 100 100 NA 100 62186.805 1610.059 280.376 NA 27.808 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1730558976 NA
OWID_WRL World 1909 2890.654 4.007 111.366 NA NA NA 1.661 NA 100 66995.701 100 NA NA NA 6.024 2726.523 NA 23.523 134.584 NA 0.003 1.567 NA 0.014 0.077 NA 100 100 100 NA 100 64913.328 1744.643 303.899 NA 33.831 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1740369408 NA
OWID_WRL World 1910 3032.156 4.895 141.502 NA NA NA 1.733 NA 100 70027.857 100 NA NA NA 7.040 2856.120 NA 24.915 144.080 NA 0.004 1.632 NA 0.014 0.082 NA 100 100 100 NA 100 67769.448 1888.723 328.814 NA 40.871 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1750000000 NA
OWID_WRL World 1911 3087.264 1.817 55.108 NA NA NA 1.755 NA 100 73115.122 100 NA NA NA 7.214 2901.556 NA 25.718 152.777 NA 0.004 1.649 NA 0.015 0.087 NA 100 100 100 NA 100 70671.004 2041.500 354.532 NA 48.085 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1759443072 NA
OWID_WRL World 1912 3233.403 4.734 146.139 NA NA NA 1.828 NA 100 76348.525 100 NA NA NA 7.583 3040.508 NA 28.315 156.997 NA 0.004 1.719 NA 0.016 0.089 NA 100 100 100 NA 100 73711.512 2198.497 382.847 NA 55.668 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1768814592 NA
OWID_WRL World 1913 3498.266 8.191 264.863 NA NA NA 1.967 NA 100 79846.791 100 0.879 NA NA 8.465 3278.396 NA 29.598 181.807 NA 0.005 1.844 NA 0.017 0.102 NA 100 100 100 NA 100 76989.908 2380.304 412.445 NA 64.133 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1778264832 3.98137e+12
OWID_WRL World 1914 3173.996 -9.269 -324.270 NA NA NA 1.775 NA 100 83020.786 100 NA NA NA 8.062 2949.976 NA 30.136 185.822 NA 0.005 1.650 NA 0.017 0.104 NA 100 100 100 NA 100 79939.884 2566.126 442.582 NA 72.195 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1787947136 NA
OWID_WRL World 1915 3130.389 -1.374 -43.607 NA NA NA 1.741 NA 100 86151.175 100 NA NA NA 7.867 2893.297 NA 31.866 197.359 NA 0.004 1.609 NA 0.018 0.110 NA 100 100 100 NA 100 82833.181 2763.485 474.447 NA 80.062 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1798018432 NA
OWID_WRL World 1916 3378.662 7.931 248.274 NA NA NA 1.868 NA 100 89529.838 100 NA NA NA 8.390 3116.991 NA 38.377 214.905 NA 0.005 1.723 NA 0.021 0.119 NA 100 100 100 NA 100 85950.172 2978.390 512.824 NA 88.452 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1808639488 NA
OWID_WRL World 1917 3533.556 4.584 154.893 NA NA NA 1.942 NA 100 93063.393 100 NA NA NA 8.457 3245.537 NA 40.509 239.052 NA 0.005 1.783 NA 0.022 0.131 NA 100 100 100 NA 100 89195.709 3217.441 553.333 NA 96.909 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1819975424 NA
OWID_WRL World 1918 3483.435 -1.418 -50.121 NA NA NA 1.901 NA 100 96546.828 100 NA NA NA 6.479 3195.730 NA 36.519 244.706 NA 0.004 1.744 NA 0.020 0.134 NA 100 100 100 NA 100 92391.439 3462.148 589.852 NA 103.389 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1832196096 NA
OWID_WRL World 1919 3019.921 -13.306 -463.513 NA NA NA 1.636 NA 100 99566.749 100 NA NA NA 7.354 2701.550 NA 37.948 273.069 NA 0.004 1.464 NA 0.021 0.148 NA 100 100 100 NA 100 95092.989 3735.217 627.800 NA 110.743 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1845476992 NA
OWID_WRL World 1920 3513.395 16.341 493.473 NA NA NA 1.889 NA 100 103080.144 100 NA NA NA 9.015 3112.383 NA 41.685 350.311 NA 0.005 1.673 NA 0.022 0.188 NA 100 100 100 NA 100 98205.372 4085.528 669.486 NA 119.758 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1860000000 NA
OWID_WRL World 1921 3083.123 -12.247 -430.272 NA NA NA 1.644 NA 100 106163.267 100 NA NA NA 8.886 2654.889 NA 34.993 384.356 NA 0.005 1.415 NA 0.019 0.205 NA 100 100 100 NA 100 100860.261 4469.884 704.479 NA 128.643 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1875909120 NA
OWID_WRL World 1922 3234.231 4.901 151.109 NA NA NA 1.708 NA 100 109397.498 100 NA NA NA 10.384 2757.275 NA 40.107 426.464 NA 0.005 1.456 NA 0.021 0.225 NA 100 100 100 NA 100 103617.536 4896.348 744.586 NA 139.028 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1893171584 NA
OWID_WRL World 1923 3670.605 13.492 436.374 NA NA NA 1.920 NA 100 113068.104 100 NA NA NA 12.431 3131.989 NA 52.526 473.659 NA 0.007 1.638 NA 0.027 0.248 NA 100 100 100 NA 100 106749.525 5370.008 797.112 NA 151.459 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1911708672 NA
OWID_WRL World 1924 3682.986 0.337 12.381 NA NA NA 1.907 NA 100 116751.090 100 NA NA NA 13.500 3138.818 NA 59.711 470.958 NA 0.007 1.625 NA 0.031 0.244 NA 100 100 100 NA 100 109888.343 5840.966 856.823 NA 164.959 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1931439872 NA
OWID_WRL World 1925 3709.804 0.728 26.817 NA NA NA 1.900 NA 100 120460.894 100 NA NA NA 14.341 3138.599 NA 63.926 492.938 NA 0.007 1.608 NA 0.033 0.252 NA 100 100 100 NA 100 113026.942 6333.903 920.749 NA 179.300 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1952281984 NA
OWID_WRL World 1926 3642.200 -1.822 -67.604 NA NA NA 1.845 NA 100 124103.094 100 NA NA NA 14.651 3067.560 NA 69.148 490.840 NA 0.007 1.554 NA 0.035 0.249 NA 100 100 100 NA 100 116094.502 6824.743 989.897 NA 193.951 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1974148992 NA
OWID_WRL World 1927 3978.374 9.230 336.174 NA NA NA 1.992 NA 100 128081.467 100 NA NA NA 15.355 3349.093 NA 76.021 537.905 NA 0.008 1.677 NA 0.038 0.269 NA 100 100 100 NA 100 119443.595 7362.649 1065.917 NA 209.306 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 1996950912 NA
OWID_WRL World 1928 3959.653 -0.471 -18.721 NA NA NA 1.960 NA 100 132041.120 100 NA NA NA 35.673 3291.700 NA 82.628 549.653 NA 0.018 1.629 NA 0.041 0.272 NA 100 100 100 NA 100 122735.295 7912.301 1148.546 NA 244.979 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2020593536 NA
OWID_WRL World 1929 4252.190 7.388 292.537 NA NA NA 2.079 NA 100 136293.310 100 0.835 NA NA 36.938 3509.547 NA 102.901 602.804 NA 0.018 1.716 NA 0.050 0.295 NA 100 100 100 NA 100 126244.842 8515.106 1251.446 NA 281.917 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2044978048 5.08999e+12
OWID_WRL World 1930 3919.399 -7.826 -332.791 NA NA NA 1.893 NA 100 140212.709 100 NA NA NA 35.625 3202.022 NA 104.232 577.520 NA 0.017 1.547 NA 0.050 0.279 NA 100 100 100 NA 100 129446.863 9092.626 1355.679 NA 317.541 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2070000000 NA
OWID_WRL World 1931 3502.982 -10.624 -416.416 NA NA NA 1.672 NA 100 143715.692 100 NA NA NA 31.021 2818.368 NA 92.901 560.692 NA 0.015 1.345 NA 0.044 0.268 NA 100 100 100 NA 100 132265.231 9653.318 1448.580 NA 348.563 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2095524352 NA
OWID_WRL World 1932 3157.845 -9.853 -345.137 NA NA NA 1.489 NA 100 146873.537 100 NA NA NA 24.851 2507.728 NA 88.235 537.031 NA 0.012 1.182 NA 0.042 0.253 NA 100 100 100 NA 100 134772.959 10190.349 1536.815 NA 373.414 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2121306496 NA
OWID_WRL World 1933 3324.972 5.292 167.126 NA NA NA 1.549 NA 100 150198.508 100 NA NA NA 23.991 2623.163 NA 90.935 586.882 NA 0.011 1.222 NA 0.042 0.273 NA 100 100 100 NA 100 137396.122 10777.231 1627.750 NA 397.405 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2147063296 NA
OWID_WRL World 1934 3616.315 8.762 291.344 NA NA NA 1.665 NA 100 153814.824 100 NA NA NA 28.718 2864.469 NA 101.973 621.154 NA 0.013 1.319 NA 0.047 0.286 NA 100 100 100 NA 100 140260.592 11398.385 1729.723 NA 426.123 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2172497152 NA
OWID_WRL World 1935 3794.457 4.926 178.141 NA NA NA 1.727 NA 100 157609.280 100 NA NA NA 32.331 2981.135 NA 111.400 669.591 NA 0.015 1.357 NA 0.051 0.305 NA 100 100 100 NA 100 143241.727 12067.976 1841.123 NA 458.454 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2197296384 NA
OWID_WRL World 1936 4168.554 9.859 374.098 NA NA NA 1.877 NA 100 161777.834 100 NA NA NA 39.091 3273.864 NA 125.565 730.035 NA 0.018 1.474 NA 0.057 0.329 NA 100 100 100 NA 100 146515.591 12798.011 1966.689 NA 497.545 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2221135616 NA
OWID_WRL World 1937 4456.655 6.911 288.100 NA NA NA 1.986 NA 100 166234.489 100 NA NA NA 41.148 3452.448 NA 140.613 822.446 NA 0.018 1.539 NA 0.063 0.367 NA 100 100 100 NA 100 149968.039 13620.457 2107.301 NA 538.692 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2243677440 NA
OWID_WRL World 1938 4193.546 -5.904 -263.109 NA NA NA 1.852 NA 100 170428.035 100 NA NA NA 38.920 3221.120 NA 135.532 797.975 NA 0.017 1.422 NA 0.060 0.352 NA 100 100 100 NA 100 153189.159 14418.432 2242.833 NA 577.612 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2264574208 NA
OWID_WRL World 1939 4435.793 5.777 242.247 NA NA NA 1.943 NA 100 174863.828 100 NA NA NA 36.049 3427.144 NA 141.366 831.234 NA 0.016 1.501 NA 0.062 0.364 NA 100 100 100 NA 100 156616.302 15249.666 2384.199 NA 613.661 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2283468800 NA
OWID_WRL World 1940 4847.084 9.272 411.292 NA NA NA 2.107 NA 100 179710.912 100 NA NA NA 31.651 3788.360 NA 153.570 873.504 NA 0.014 1.647 NA 0.067 0.380 NA 100 100 100 NA 100 160404.663 16123.169 2537.769 NA 645.311 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2300000000 NA
OWID_WRL World 1941 4955.476 2.236 108.392 NA NA NA 2.141 NA 100 184666.388 100 NA NA NA 43.463 3876.834 NA 153.463 881.716 NA 0.019 1.675 NA 0.066 0.381 NA 100 100 100 NA 100 164281.497 17004.885 2691.232 NA 688.774 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2314055168 NA
OWID_WRL World 1942 4935.659 -0.400 -19.817 NA NA NA 2.121 NA 100 189602.048 100 NA NA NA 38.219 3894.969 NA 166.049 836.422 NA 0.016 1.674 NA 0.071 0.360 NA 100 100 100 NA 100 168176.466 17841.308 2857.281 NA 726.993 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2326540544 NA
OWID_WRL World 1943 5018.865 1.686 83.206 NA NA NA 2.146 NA 100 194620.912 100 NA NA NA 34.653 3912.609 NA 182.900 888.703 NA 0.015 1.673 NA 0.078 0.380 NA 100 100 100 NA 100 172089.074 18730.011 3040.181 NA 761.646 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2338643968 NA
OWID_WRL World 1944 5101.040 1.637 82.175 NA NA NA 2.169 NA 100 199721.952 100 NA NA NA 22.524 3861.790 NA 197.601 1019.124 NA 0.010 1.642 NA 0.084 0.433 NA 100 100 100 NA 100 175950.864 19749.135 3237.782 NA 784.171 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2351580160 NA
OWID_WRL World 1945 4240.829 -16.863 -860.211 NA NA NA 1.792 NA 100 203962.781 100 NA NA NA 22.934 2992.181 NA 216.746 1008.968 NA 0.010 1.264 NA 0.092 0.426 NA 100 100 100 NA 100 178943.046 20758.103 3454.528 NA 807.105 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2366593024 NA
OWID_WRL World 1946 4629.673 9.169 388.844 NA NA NA 1.941 NA 100 208592.454 100 NA NA NA 36.312 3228.828 NA 223.895 1140.638 NA 0.015 1.354 NA 0.094 0.478 NA 100 100 100 NA 100 182171.874 21898.741 3678.423 NA 843.417 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2384963584 NA
OWID_WRL World 1947 5125.894 10.718 496.221 NA NA NA 2.129 NA 100 213718.348 100 NA NA NA 43.237 3612.469 NA 247.966 1222.223 NA 0.018 1.500 NA 0.103 0.508 NA 100 100 100 NA 100 185784.343 23120.964 3926.388 NA 886.653 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2408024320 NA
OWID_WRL World 1948 5396.503 5.279 270.609 NA NA NA 2.214 NA 100 219114.852 100 NA NA NA 51.766 3723.983 NA 280.214 1340.541 NA 0.021 1.528 NA 0.115 0.550 NA 100 100 100 NA 100 189508.326 24461.505 4206.602 NA 938.419 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2437183232 NA
OWID_WRL World 1949 5239.276 -2.913 -157.227 NA NA NA 2.118 NA 100 224354.128 100 NA NA NA 58.355 3542.528 NA 300.549 1337.845 NA 0.024 1.432 NA 0.121 0.541 NA 100 100 100 NA 100 193050.854 25799.350 4507.151 NA 996.774 100 100 100 NA 100 NA NA NA NA NA NA NA NA NA 2473954560 NA
OWID_WRL World 1950 5998.350 14.488 759.074 NA NA NA 2.365 NA 100 230352.479 100 0.726 NA NA 66.939 3854.980 73.624 353.283 1649.525 NA 0.026 1.520 0.029 0.139 0.650 NA 100 100 100 100 100 196905.833 27448.875 4860.434 73.624 1063.712 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 2536431104 8.26090e+12
OWID_WRL World 1951 6373.785 6.259 375.434 NA NA NA 2.467 NA 100 236726.264 100 0.728 NA NA 75.576 4058.695 79.875 416.327 1743.311 NA 0.029 1.571 0.031 0.161 0.675 NA 100 100 100 100 100 200964.528 29192.186 5276.761 153.500 1139.289 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 2584034048 8.76367e+12
OWID_WRL World 1952 6460.163 1.355 86.378 NA NA NA 2.456 NA 100 243186.427 100 0.704 NA NA 81.134 4007.545 85.364 447.229 1838.891 NA 0.031 1.523 0.032 0.170 0.699 NA 100 100 100 100 100 204972.073 31031.077 5723.991 238.863 1220.423 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 2630862080 9.16940e+12
OWID_WRL World 1953 6641.785 2.811 181.622 NA NA NA 2.480 NA 100 249828.212 100 0.685 NA NA 90.026 4042.021 81.348 474.686 1953.705 NA 0.034 1.510 0.030 0.177 0.730 NA 100 100 100 100 100 209014.094 32984.782 6198.676 320.212 1310.449 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 2677608960 9.69107e+12
OWID_WRL World 1954 6784.944 2.155 143.159 NA NA NA 2.490 NA 100 256613.156 100 0.682 NA NA 97.787 4037.623 77.612 501.531 2070.391 NA 0.036 1.482 0.028 0.184 0.760 NA 100 100 100 100 100 213051.717 35055.173 6700.207 397.824 1408.235 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 2724847104 9.94678e+12
OWID_WRL World 1955 7437.038 9.611 652.094 NA NA NA 2.682 NA 100 264050.194 100 0.702 NA NA 108.186 4370.550 96.836 547.454 2314.013 NA 0.039 1.576 0.035 0.197 0.834 NA 100 100 100 100 100 217422.267 37369.185 7247.660 494.659 1516.422 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 2773019904 1.06071e+13
OWID_WRL World 1956 7917.910 6.466 480.872 NA NA NA 2.805 NA 100 271968.104 100 0.713 NA NA 117.213 4594.487 108.174 587.533 2510.504 NA 0.042 1.628 0.038 0.208 0.889 NA 100 100 100 100 100 222016.754 39879.689 7835.193 602.833 1633.635 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 2822443008 1.11100e+13
OWID_WRL World 1957 8179.340 3.302 261.429 NA NA NA 2.847 NA 100 280147.444 100 0.711 NA NA 123.183 4678.644 106.386 647.176 2623.951 NA 0.043 1.628 0.037 0.225 0.913 NA 100 100 100 100 100 226695.398 42503.641 8482.369 709.219 1756.818 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 2873306112 1.14910e+13
OWID_WRL World 1958 8412.113 2.846 232.773 NA NA NA 2.875 NA 100 288559.557 100 0.713 NA NA 130.396 4750.659 95.115 706.630 2729.314 NA 0.045 1.624 0.033 0.242 0.933 NA 100 100 100 100 100 231446.056 45232.955 9188.998 804.333 1887.214 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 2925687040 1.18390e+13
OWID_WRL World 1959 8848.509 5.188 436.396 NA NA NA 2.970 NA 100 297408.066 100 0.719 NA NA 145.957 4943.832 91.694 759.285 2907.741 NA 0.049 1.659 0.031 0.255 0.976 NA 100 100 100 100 100 236389.888 48140.695 9948.283 896.027 2033.171 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 2979576064 1.23121e+13
OWID_WRL World 1960 9334.894 5.497 486.386 NA NA NA 3.076 NA 100 306742.960 100 0.724 NA NA 156.941 5130.917 89.140 835.374 3122.522 NA 0.052 1.691 0.029 0.275 1.029 NA 100 100 100 100 100 241520.806 51263.217 10783.657 985.167 2190.112 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 3034949888 1.29028e+13
OWID_WRL World 1961 9356.003 0.226 21.109 NA NA NA 3.026 NA 100 316098.963 100 0.698 NA NA 165.445 4915.325 86.219 882.812 3306.202 NA 0.054 1.590 0.028 0.286 1.069 NA 100 100 100 100 100 246436.130 54569.420 11666.470 1071.386 2355.557 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 3091844096 1.34101e+13
OWID_WRL World 1962 9687.509 3.543 331.506 NA NA NA 3.075 NA 100 325786.472 100 0.687 NA NA 177.697 4901.276 85.931 968.788 3553.818 NA 0.056 1.556 0.027 0.308 1.128 NA 100 100 100 100 100 251337.406 58123.238 12635.257 1157.317 2533.254 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 3150420992 1.41374e+13
OWID_WRL World 1963 10236.031 5.662 548.522 NA NA NA 3.188 NA 100 336022.503 100 0.696 NA NA 187.210 5101.000 90.506 1049.370 3807.944 NA 0.058 1.589 0.028 0.327 1.186 NA 100 100 100 100 100 256438.406 61931.182 13684.627 1247.823 2720.465 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 3211001088 1.47203e+13
OWID_WRL World 1964 10769.609 5.213 533.578 NA NA NA 3.289 NA 100 346792.112 100 0.677 NA NA 205.788 5195.154 112.792 1155.366 4100.509 NA 0.063 1.587 0.034 0.353 1.252 NA 100 100 100 100 100 261633.560 66031.691 14839.993 1360.615 2926.253 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 3273978112 1.58570e+13
OWID_WRL World 1965 11269.289 4.640 499.680 NA NA NA 3.374 NA 100 358061.401 100 0.671 NA 0.262 215.178 5280.001 130.443 1233.892 4409.775 NA 0.064 1.581 0.039 0.369 1.320 NA 100 100 100 100 100 266913.562 70441.466 16073.885 1491.058 3141.431 100 100 100 100 100 NA NA NA NA NA NA 43070.29 12896.90 2.571 3339584000 1.67555e+13
OWID_WRL World 1966 11793.838 4.655 524.549 NA NA NA 3.461 NA 100 369855.239 100 0.666 NA 0.260 230.268 5327.529 144.566 1342.855 4748.620 NA 0.068 1.563 0.042 0.394 1.393 NA 100 100 100 100 100 272241.091 75190.086 17416.740 1635.624 3371.699 100 100 100 100 100 NA NA NA NA NA NA 45406.99 13323.95 2.570 3407922944 1.76661e+13
OWID_WRL World 1967 12171.497 3.202 377.659 NA NA NA 3.499 NA 100 382026.736 100 0.661 NA 0.258 238.147 5243.604 190.783 1436.176 5062.786 NA 0.068 1.507 0.055 0.413 1.455 NA 100 100 100 100 100 277484.695 80252.871 18852.917 1826.407 3609.846 100 100 100 100 100 NA NA NA NA NA NA 47126.35 13546.84 2.559 3478769920 1.84194e+13
OWID_WRL World 1968 12835.996 5.459 664.499 NA NA NA 3.614 NA 100 394862.732 100 0.658 NA 0.257 254.905 5301.229 203.800 1562.833 5513.230 NA 0.072 1.493 0.057 0.440 1.552 NA 100 100 100 100 100 282785.924 85766.101 20415.749 2030.207 3864.751 100 100 100 100 100 NA NA NA NA NA NA 49985.64 14074.12 2.567 3551599104 1.94729e+13
OWID_WRL World 1969 13691.842 6.668 855.846 NA NA NA 3.776 NA 100 408554.574 100 0.665 NA 0.256 268.359 5501.878 244.035 1712.032 5965.538 NA 0.074 1.517 0.067 0.472 1.645 NA 100 100 100 100 100 288287.801 91731.639 22127.782 2274.242 4133.110 100 100 100 100 100 NA NA NA NA NA NA 53394.06 14726.63 2.591 3625680896 2.06074e+13
OWID_WRL World 1970 14826.863 8.290 1135.020 NA NA NA 4.007 NA 100 423381.436 100 0.680 NA 0.261 282.282 5680.360 277.745 1794.121 6792.355 NA 0.076 1.535 0.075 0.485 1.836 NA 100 100 100 100 100 293968.161 98523.993 23921.903 2551.987 4415.392 100 100 100 100 100 NA NA NA NA NA NA 56709.19 15325.00 2.596 3700436992 2.18429e+13
OWID_WRL World 1971 15425.831 4.040 598.969 NA NA NA 4.085 NA 100 438807.268 100 0.677 NA 0.261 300.044 5681.463 321.128 1936.725 7186.471 NA 0.079 1.505 0.085 0.513 1.903 NA 100 100 100 100 100 299649.624 105710.464 25858.628 2873.115 4715.436 100 100 100 100 100 NA NA NA NA NA NA 59090.43 15649.94 2.587 3775759872 2.28411e+13
OWID_WRL World 1972 16142.605 4.647 716.774 NA NA NA 4.191 NA 100 454949.873 100 0.673 NA 0.259 316.962 5675.726 346.570 2055.258 7748.089 NA 0.082 1.474 0.090 0.534 2.012 NA 100 100 100 100 100 305325.351 113458.553 27913.886 3219.685 5032.398 100 100 100 100 100 NA NA NA NA NA NA 62273.70 16168.05 2.596 3851651072 2.39881e+13
OWID_WRL World 1973 17000.713 5.316 858.108 NA NA NA 4.328 NA 100 471950.586 100 0.662 NA 0.258 335.999 5837.205 402.006 2136.413 8289.090 NA 0.086 1.486 0.102 0.544 2.110 NA 100 100 100 100 100 311162.556 121747.644 30050.298 3621.691 5368.397 100 100 100 100 100 NA NA NA NA NA NA 65857.67 16767.14 2.563 3927781120 2.56992e+13
OWID_WRL World 1974 16925.872 -0.440 -74.842 NA NA NA 4.227 NA 100 488876.457 100 0.634 NA 0.256 336.717 5847.758 391.234 2180.941 8169.223 NA 0.084 1.461 0.098 0.545 2.040 NA 100 100 100 100 100 317010.314 129916.866 32231.239 4012.925 5705.114 100 100 100 100 100 NA NA NA NA NA NA 66173.94 16527.81 2.475 4003793920 2.67355e+13
OWID_WRL World 1975 16902.973 -0.135 -22.899 NA NA NA 4.143 NA 100 505779.430 100 0.619 NA 0.254 333.850 5974.763 336.444 2193.919 8063.996 NA 0.082 1.465 0.082 0.538 1.977 NA 100 100 100 100 100 322985.077 137980.862 34425.158 4349.369 6038.964 100 100 100 100 100 NA NA NA NA NA NA 66518.52 16305.64 2.439 4079480064 2.72686e+13
OWID_WRL World 1976 17799.760 5.306 896.788 NA NA NA 4.284 NA 100 523579.190 100 0.622 NA 0.254 356.318 6242.261 395.348 2323.262 8482.571 NA 0.086 1.502 0.095 0.559 2.042 NA 100 100 100 100 100 329227.338 146463.434 36748.420 4744.717 6395.282 100 100 100 100 100 NA NA NA NA NA NA 70137.94 16881.72 2.449 4154667008 2.86389e+13
OWID_WRL World 1977 18287.936 2.743 488.176 NA NA NA 4.324 NA 100 541867.126 100 0.614 NA 0.252 371.939 6373.924 381.321 2367.022 8793.730 NA 0.088 1.507 0.090 0.560 2.079 NA 100 100 100 100 100 335601.262 155257.164 39115.442 5126.038 6767.220 100 100 100 100 100 NA NA NA NA NA NA 72630.75 17172.39 2.441 4229506048 2.97599e+13
OWID_WRL World 1978 18958.832 3.669 670.896 NA NA NA 4.404 NA 100 560825.958 100 0.610 NA 0.252 394.791 6568.674 390.089 2489.867 9115.411 NA 0.092 1.526 0.091 0.578 2.118 NA 100 100 100 100 100 342169.936 164372.575 41605.308 5516.128 7162.011 100 100 100 100 100 NA NA NA NA NA NA 75125.75 17452.70 2.415 4304534016 3.11021e+13
OWID_WRL World 1979 19464.238 2.666 505.406 NA NA NA 4.443 NA 100 580290.196 100 0.603 NA 0.250 401.223 6816.022 360.196 2630.153 9256.644 NA 0.092 1.556 0.082 0.600 2.113 NA 100 100 100 100 100 348985.958 173629.219 44235.461 5876.324 7563.234 100 100 100 100 100 NA NA NA NA NA NA 77736.77 17746.07 2.404 4380506112 3.23425e+13
OWID_WRL World 1980 19369.452 -0.487 -94.786 NA NA NA 4.345 NA 100 599659.648 100 0.585 NA 0.251 403.947 7017.390 316.485 2708.026 8923.604 NA 0.091 1.574 0.071 0.607 2.002 NA 100 100 100 100 100 356003.348 182552.823 46943.487 6192.809 7967.181 100 100 100 100 100 NA NA NA NA NA NA 77171.18 17310.71 2.329 4458002944 3.31401e+13
OWID_WRL World 1981 18841.367 -2.726 -528.085 NA NA NA 4.153 NA 100 618501.015 100 0.564 NA 0.246 403.666 6973.884 237.302 2739.036 8487.479 NA 0.089 1.537 0.052 0.604 1.871 NA 100 100 100 100 100 362977.232 191040.302 49682.523 6430.111 8370.847 100 100 100 100 100 NA NA NA NA NA NA 76739.23 16914.10 2.299 4536996864 3.33737e+13
OWID_WRL World 1982 18700.965 -0.745 -140.402 NA NA NA 4.050 NA 100 637201.980 100 0.558 NA 0.245 401.622 7099.887 235.796 2680.506 8283.154 NA 0.087 1.538 0.051 0.581 1.794 NA 100 100 100 100 100 370077.119 199323.456 52363.029 6665.908 8772.468 100 100 100 100 100 NA NA NA NA NA NA 76414.32 16549.26 2.279 4617387008 3.35294e+13
OWID_WRL World 1983 18876.275 0.937 175.310 NA NA NA 4.017 NA 100 656078.254 100 0.552 NA 0.243 411.161 7312.340 213.145 2725.148 8214.480 NA 0.087 1.556 0.045 0.580 1.748 NA 100 100 100 100 100 377389.459 207537.936 55088.177 6879.053 9183.629 100 100 100 100 100 NA NA NA NA NA NA 77623.87 16517.23 2.272 4699569152 3.41694e+13
OWID_WRL World 1984 19426.234 2.913 549.959 NA NA NA 4.061 NA 100 675504.488 100 0.549 NA 0.239 418.837 7624.128 187.119 2942.506 8253.644 NA 0.088 1.594 0.039 0.615 1.725 NA 100 100 100 100 100 385013.587 215791.580 58030.683 7066.172 9602.467 100 100 100 100 100 NA NA NA NA NA NA 81291.51 16992.33 2.298 4784011776 3.53701e+13
OWID_WRL World 1985 20116.824 3.555 690.590 NA NA NA 4.130 NA 100 695621.312 100 0.551 NA 0.241 422.731 8177.460 181.886 3064.540 8270.208 NA 0.087 1.679 0.037 0.629 1.698 NA 100 100 100 100 100 393191.047 224061.788 61095.223 7248.058 10025.197 100 100 100 100 100 NA NA NA NA NA NA 83360.79 17113.96 2.287 4870922240 3.64500e+13
OWID_WRL World 1986 20401.695 1.416 284.870 NA NA NA 4.113 NA 100 716023.007 100 0.540 NA 0.239 439.966 8268.885 170.183 3005.575 8517.086 NA 0.089 1.667 0.034 0.606 1.717 NA 100 100 100 100 100 401459.932 232578.874 64100.798 7418.240 10465.163 100 100 100 100 100 NA NA NA NA NA NA 85194.75 17174.40 2.252 4960567808 3.78313e+13
OWID_WRL World 1987 21062.704 3.240 661.009 NA NA NA 4.169 NA 100 737085.711 100 0.536 NA 0.239 458.359 8567.808 163.551 3255.566 8617.420 NA 0.091 1.696 0.032 0.644 1.706 NA 100 100 100 100 100 410027.740 241196.294 67356.363 7581.792 10923.522 100 100 100 100 100 NA NA NA NA NA NA 88171.10 17450.91 2.243 5052521984 3.93124e+13
OWID_WRL World 1988 21865.971 3.814 803.267 NA NA NA 4.250 NA 100 758951.682 100 0.533 NA 0.239 485.930 8858.933 186.185 3414.657 8920.266 NA 0.094 1.722 0.036 0.664 1.734 NA 100 100 100 100 100 418886.673 250116.560 70771.020 7767.976 11409.453 100 100 100 100 100 NA NA NA NA NA NA 91500.97 17782.97 2.234 5145425920 4.09526e+13
OWID_WRL World 1989 22193.362 1.497 327.391 NA NA NA 4.237 NA 100 781145.044 100 0.525 NA 0.238 497.250 8882.261 151.453 3592.678 9069.719 NA 0.095 1.696 0.029 0.686 1.732 NA 100 100 100 100 100 427768.934 259186.278 74363.699 7919.430 11906.703 100 100 100 100 100 NA NA NA NA NA NA 93310.19 17815.99 2.205 5237441024 4.23267e+13
OWID_WRL World 1990 22697.612 2.272 504.250 NA NA NA 4.261 NA 100 803842.656 100 0.525 NA 0.240 499.196 8720.617 247.908 3860.862 9218.816 150.213 0.094 1.637 0.047 0.725 1.731 0.028 100 100 100 100 100 436489.551 268405.094 78224.561 8167.337 12405.899 100 100 100 100 100 34967.34 6.564 7415.58 1.392 2460.54 0.462 94383.41 17717.16 2.183 5327230976 4.32400e+13
OWID_WRL World 1991 23169.529 2.079 471.917 NA NA NA 4.279 NA 100 827012.185 100 0.530 NA 0.244 512.831 8639.866 262.648 3939.118 9676.619 138.447 0.095 1.596 0.049 0.728 1.787 0.026 100 100 100 100 100 445129.417 278081.713 82163.679 8429.985 12918.730 100 100 100 100 100 35125.44 6.488 7387.74 1.364 2447.93 0.452 94998.44 17545.88 2.176 5414288896 4.36640e+13
OWID_WRL World 1992 22444.951 -3.127 -724.578 NA NA NA 4.082 NA 100 849457.136 100 0.501 NA 0.235 534.533 8423.192 232.040 3966.600 9160.068 128.518 0.097 1.532 0.042 0.721 1.666 0.023 100 100 100 100 100 453552.609 287241.782 86130.278 8662.025 13453.263 100 100 100 100 100 34985.53 6.362 7322.48 1.332 2440.49 0.444 95643.59 17393.16 2.136 5498919936 4.47760e+13
OWID_WRL World 1993 22682.603 1.059 237.652 NA NA NA 4.064 NA 100 872139.739 100 0.500 NA 0.235 555.314 8522.452 228.386 4074.315 9183.989 118.147 0.099 1.527 0.041 0.730 1.645 0.021 100 100 100 100 100 462075.061 296425.770 90204.593 8890.411 14008.577 100 100 100 100 100 35079.63 6.285 7300.62 1.308 2428.77 0.435 96369.91 17265.65 2.121 5581598208 4.54466e+13
OWID_WRL World 1994 22843.788 0.711 161.185 NA NA NA 4.034 NA 100 894983.527 100 0.491 NA 0.234 591.947 8572.822 231.587 4112.049 9221.056 114.327 0.105 1.514 0.041 0.726 1.628 0.020 100 100 100 100 100 470647.883 305646.826 94316.642 9121.998 14600.524 100 100 100 100 100 35287.61 6.231 7274.33 1.285 2514.99 0.444 97641.65 17241.58 2.100 5663150080 4.65049e+13
OWID_WRL World 1995 23332.159 2.138 488.371 NA NA NA 4.062 NA 100 918315.686 100 0.483 NA 0.234 625.866 8822.304 230.257 4220.642 9314.526 118.564 0.109 1.536 0.040 0.735 1.622 0.021 100 100 100 100 100 479470.188 314961.352 98537.284 9352.255 15226.390 100 100 100 100 100 36012.63 6.269 7283.49 1.268 2570.66 0.448 99620.58 17342.77 2.062 5744212992 4.83222e+13
OWID_WRL World 1996 24050.844 3.080 718.685 NA NA NA 4.129 NA 100 942366.530 100 0.483 NA 0.234 639.119 9035.080 233.118 4406.063 9623.161 114.303 0.110 1.551 0.040 0.756 1.652 0.020 100 100 100 100 100 488505.267 324584.513 102943.347 9585.373 15865.509 100 100 100 100 100 36025.05 6.185 7152.83 1.228 2577.46 0.442 102592.22 17612.72 2.061 5824891904 4.97675e+13
OWID_WRL World 1997 24191.148 0.583 140.305 NA NA NA 4.097 NA 100 966557.678 100 0.471 NA 0.233 658.367 8986.534 238.107 4422.390 9771.633 114.117 0.111 1.522 0.040 0.749 1.655 0.019 100 100 100 100 100 497491.802 334356.147 107365.737 9823.480 16523.875 100 100 100 100 100 37342.50 6.324 7369.05 1.248 2587.71 0.438 103650.06 17552.79 2.018 5905046016 5.13524e+13
OWID_WRL World 1998 24112.119 -0.327 -79.029 NA NA NA 4.029 NA 100 990669.797 100 0.463 NA 0.231 654.507 8749.415 226.832 4495.893 9871.746 113.726 0.109 1.462 0.038 0.751 1.649 0.019 100 100 100 100 100 506241.217 344227.893 111861.629 10050.312 17178.382 100 100 100 100 100 36976.63 6.178 7274.29 1.215 2599.16 0.434 104270.80 17422.62 2.000 5984794112 5.21305e+13
OWID_WRL World 1999 24431.051 1.323 318.932 NA NA NA 4.029 NA 100 1015100.848 100 0.452 NA 0.230 684.409 8679.499 219.234 4628.797 10104.990 114.122 0.113 1.431 0.036 0.763 1.666 0.019 100 100 100 100 100 514920.716 354332.883 116490.427 10269.546 17862.791 100 100 100 100 100 36810.09 6.070 7207.23 1.188 2572.36 0.424 106165.38 17506.79 1.966 6064239104 5.40115e+13
OWID_WRL World 2000 25119.042 2.816 687.992 NA NA NA 4.089 NA 100 1040219.890 100 0.438 NA 0.231 715.796 8999.104 264.501 4745.742 10280.736 113.164 0.117 1.465 0.043 0.772 1.673 0.018 100 100 100 100 100 523919.820 364613.620 121236.168 10534.047 18578.587 100 100 100 100 100 37420.92 6.091 7173.99 1.168 2554.89 0.416 108822.06 17713.38 1.899 6143494144 5.73017e+13
OWID_WRL World 2001 25332.203 0.849 213.160 NA NA NA 4.071 NA 100 1065552.092 100 0.432 NA 0.230 747.540 9048.280 266.260 4791.210 10367.720 111.193 0.120 1.454 0.043 0.770 1.666 0.018 100 100 100 100 100 532968.100 374981.339 126027.378 10800.307 19326.127 100 100 100 100 100 38379.96 6.168 7262.65 1.167 2592.42 0.417 110048.80 17685.26 1.877 6222626816 5.86318e+13
OWID_WRL World 2002 25911.186 2.286 578.984 NA NA NA 4.112 NA 100 1091463.279 100 0.428 NA 0.230 787.887 9437.304 276.993 4936.982 10358.792 113.229 0.125 1.498 0.044 0.783 1.644 0.018 100 100 100 100 100 542405.404 385340.130 130964.360 11077.300 20114.014 100 100 100 100 100 39824.70 6.320 7561.80 1.200 2662.79 0.423 112538.21 17858.18 1.860 6301772800 6.05064e+13
OWID_WRL World 2003 27176.184 4.882 1264.998 NA NA NA 4.259 NA 100 1118639.463 100 0.436 NA 0.233 846.510 10210.176 277.337 5106.119 10621.093 114.949 0.133 1.600 0.043 0.800 1.664 0.018 100 100 100 100 100 552615.580 395961.223 136070.479 11354.637 20960.524 100 100 100 100 100 40678.67 6.375 7586.58 1.189 2676.14 0.419 116667.07 18282.98 1.869 6381185024 6.24252e+13
OWID_WRL World 2004 28470.451 4.763 1294.267 NA NA NA 4.406 NA 100 1147109.914 100 0.431 NA 0.233 905.653 10877.645 301.041 5274.069 10992.582 119.461 0.140 1.684 0.047 0.816 1.701 0.018 100 100 100 100 100 563493.225 406953.806 141344.548 11655.678 21866.177 100 100 100 100 100 42452.22 6.570 7770.13 1.203 2742.89 0.425 122395.79 18943.32 1.855 6461158912 6.59958e+13
OWID_WRL World 2005 29410.889 3.303 940.438 NA NA NA 4.496 NA 100 1176520.803 100 0.416 NA 0.232 957.464 11537.730 321.168 5399.904 11071.852 122.770 0.146 1.764 0.049 0.825 1.692 0.019 100 100 100 100 100 575030.956 418025.658 146744.452 11976.846 22823.641 100 100 100 100 100 43354.52 6.627 7749.03 1.185 2740.70 0.419 126626.72 19356.24 1.790 6541906944 7.07299e+13
OWID_WRL World 2006 30374.554 3.277 963.665 NA NA NA 4.586 NA 100 1206895.357 100 0.404 NA 0.233 1045.562 12194.676 322.802 5524.521 11159.281 127.711 0.158 1.841 0.049 0.834 1.685 0.019 100 100 100 100 100 587225.632 429184.940 152268.973 12299.648 23869.204 100 100 100 100 100 43723.50 6.601 7927.19 1.197 2774.44 0.419 130323.33 19675.85 1.736 6623518208 7.50739e+13
OWID_WRL World 2007 31293.862 3.027 919.308 NA NA NA 4.667 NA 100 1238189.220 100 0.392 NA 0.233 1120.179 12774.790 337.991 5710.415 11221.838 128.649 0.167 1.905 0.050 0.852 1.673 0.019 100 100 100 100 100 600000.422 440406.778 157979.388 12637.639 24989.382 100 100 100 100 100 44584.43 6.648 7945.85 1.185 2822.20 0.421 134465.27 20051.65 1.684 6705947136 7.98616e+13
OWID_WRL World 2008 31946.034 2.084 652.172 NA NA NA 4.705 NA 100 1270135.253 100 0.385 NA 0.235 1136.902 13260.656 351.570 5873.324 11199.617 123.965 0.167 1.953 0.052 0.865 1.650 0.018 100 100 100 100 100 613261.078 451606.395 163852.712 12989.210 26126.284 100 100 100 100 100 44952.27 6.621 8017.25 1.181 2802.99 0.413 136130.34 20051.34 1.641 6789088768 8.29638e+13
OWID_WRL World 2009 31464.200 -1.508 -481.833 NA NA NA 4.578 NA 100 1301599.454 100 0.382 NA 0.234 1168.219 13096.209 342.766 5764.762 10989.512 102.732 0.170 1.906 0.050 0.839 1.599 0.015 100 100 100 100 100 626357.287 462595.907 169617.474 13331.976 27294.503 100 100 100 100 100 44936.19 6.538 8100.53 1.179 2803.03 0.408 134213.76 19528.34 1.629 6872766976 8.23905e+13
OWID_WRL World 2010 33131.911 5.300 1667.711 NA NA NA 4.763 NA 100 1334731.365 100 0.374 NA 0.235 1242.448 13930.110 350.361 6206.111 11288.151 114.729 0.179 2.002 0.050 0.892 1.623 0.016 100 100 100 100 100 640287.397 473884.058 175823.585 13682.337 28536.951 100 100 100 100 100 46552.37 6.692 8170.01 1.174 2860.55 0.411 140722.29 20227.95 1.591 6956824064 8.84541e+13
OWID_WRL World 2011 34209.583 3.253 1077.672 NA NA NA 4.858 NA 100 1368940.948 100 0.364 NA 0.237 1333.891 14748.066 343.432 6372.084 11294.423 117.687 0.189 2.095 0.049 0.905 1.604 0.017 100 100 100 100 100 655035.463 485178.481 182195.670 14025.769 29870.842 100 100 100 100 100 47802.54 6.789 8280.11 1.176 2943.30 0.418 144255.09 20487.31 1.535 7041193984 9.39521e+13
OWID_WRL World 2012 34760.008 1.609 550.426 NA NA NA 4.878 NA 100 1403700.956 100 0.360 NA 0.238 1371.644 14901.935 348.956 6497.149 11523.496 116.828 0.192 2.091 0.049 0.912 1.617 0.016 100 100 100 100 100 669937.398 496701.978 188692.819 14374.725 31242.486 100 100 100 100 100 48348.77 6.785 8374.14 1.175 2970.41 0.417 146252.98 20524.35 1.513 7125828096 9.66492e+13
OWID_WRL World 2013 34987.264 0.654 227.255 NA NA NA 4.852 NA 100 1438688.219 100 0.352 NA 0.235 1427.393 14921.136 349.063 6540.736 11629.569 119.366 0.198 2.069 0.048 0.907 1.613 0.017 100 100 100 100 100 684858.534 508331.547 195233.555 14723.788 32669.879 100 100 100 100 100 48961.60 6.790 8339.46 1.157 2941.00 0.408 149089.93 20676.55 1.502 7210582016 9.92797e+13
OWID_WRL World 2014 35244.868 0.736 257.605 NA NA NA 4.831 NA 100 1473933.087 100 0.346 NA 0.234 1483.543 14944.736 360.754 6590.456 11744.752 120.627 0.203 2.049 0.049 0.903 1.610 0.017 100 100 100 100 100 699803.270 520076.299 201824.011 15084.542 34153.422 100 100 100 100 100 49440.79 6.777 8477.25 1.162 2999.32 0.411 150489.50 20628.31 1.475 7295290880 1.01999e+14
OWID_WRL World 2015 35209.447 -0.101 -35.422 NA NA NA 4.771 NA 100 1509142.534 100 0.335 NA 0.232 1428.375 14624.451 362.053 6762.248 11914.683 117.635 0.194 1.982 0.049 0.916 1.615 0.016 100 100 100 100 100 714427.722 531990.982 208586.259 15446.595 35581.797 100 100 100 100 100 49854.98 6.756 8660.01 1.173 3052.82 0.414 151720.06 20558.84 1.447 7379796992 1.04855e+14
OWID_WRL World 2016 35220.412 0.031 10.966 NA NA NA 4.719 NA 100 1544362.946 100 0.329 NA 0.229 1463.585 14364.382 371.409 6939.908 11969.329 111.800 0.196 1.924 0.050 0.930 1.604 0.015 100 100 100 100 100 728792.104 543960.311 215526.166 15818.004 37045.382 100 100 100 100 100 49358.03 6.613 8550.06 1.146 3054.00 0.409 153848.43 20612.00 1.444 7464022016 1.06561e+14
OWID_WRL World 2017 35696.349 1.351 475.936 NA NA NA 4.729 NA 100 1580059.295 100 NA NA NA 1476.475 14413.361 403.984 7114.554 12174.822 113.152 0.196 1.910 0.054 0.943 1.613 0.015 100 100 100 100 100 743205.465 556135.133 222640.721 16221.989 38521.857 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 7547858944 NA
OWID_WRL World 2018 36419.712 2.026 723.363 NA NA NA 4.773 NA 100 1616479.007 100 NA NA NA 1514.612 14618.299 429.496 7489.099 12253.085 115.121 0.198 1.916 0.056 0.981 1.606 0.015 100 100 100 100 100 757823.764 568388.218 230129.820 16651.484 40036.469 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 7631091200 NA
OWID_WRL World 2019 36441.388 0.060 21.676 NA NA NA 4.724 NA 100 1652920.394 100 NA NA NA 1563.761 14362.167 429.496 7615.714 12355.129 115.121 0.203 1.862 0.056 0.987 1.602 0.015 100 100 100 100 100 772185.931 580743.347 237745.534 17080.980 41600.230 100 100 100 100 100 NA NA NA NA NA NA NA NA NA 7713467904 NA

4.1.3.2 Data mapping

OGS.MAP.OWID = function(owid_data, geoscale, geoname.filter){
  owid_data_OGS = owid_data %>% 
    filter(country == geoname.filter) %>% 
    add_column(data.provider = "OWID",
               data.source = "OWID",
               geo.scale = geoscale,
               sector = "All",
               geo.code.iso2c = NA,
               unit = "MtCO₂",
               gas = "CO2") %>% 
    rename(geo.code.iso3c = iso_code,
           geo.name = country,
           value = co2) %>% 
    select(data.source, data.provider, geo.scale, geo.code.iso2c, geo.code.iso3c, geo.name,
           year, sector, gas, value)  
  
  return(owid_data_OGS)
}

owid_data_OGS = OGS.MAP.OWID(owid_data = ghg_emissions_owid,
                             geoscale = "World",
                             geoname.filter = "World")

# plot timeserie
owid_data_OGS %>% 
  # filter(year >= 1990 & year < 2017) %>% 
  plot_ly() %>% 
  add_trace(y = ~value, 
            x = ~year, 
            type = 'scatter',
            mode = 'lines+markers',
            orientation = "v",
            hoverinfo = 'text',
            text = ~paste('</br> Year: ', year,
                          '</br> Value: ', value,
                          '</br> Gas: ', gas,
                          '</br> Sector: ', sector,
                          '</br> Source: ', data.provider)) %>% 
  layout(title = "World GHG emissions (source: WRI - CAIT)",
         yaxis = list(title = "GHG emissions"), 
         xaxis = list(title = "Years"))

4.2 Data comparison

OGS_ghg_emission = bind_rows(Worldbank_data_OGS, 
                             wri_data_OGS,
                             owid_data_OGS)

# plot timeserie
OGS_ghg_emission %>% 
  filter(year >= 1990) %>%
  plot_ly() %>% 
  add_trace(y = ~value, 
            x = ~year, 
            color = ~data.provider,
            type = 'scatter',
            # type = "line",
            mode = 'lines+markers',
            orientation = "v",
            hoverinfo = 'text',
            text = ~paste('</br> Year: ', year,
                          '</br> Value: ', value,
                          '</br> Gas: ', gas,
                          '</br> Sector: ', sector,
                          '</br> Source: ', data.provider)) %>% 
  layout(title = "World GHG emissions",
         yaxis = list(title = "GHG emissions (MtCO₂)"), 
         xaxis = list(title = "Years"))

5 Country scale: France use case

5.1 Data sources

5.1.1 European Environmental Agency Data

5.1.1.1 Data Exploration

ghg_emissions_eea <- readr::read_csv(file = "https://raw.githubusercontent.com/OpenGeoScales/CarbonData/main/datasets/raw/eea/UNFCCC_v23.csv")

The table below describes a complete description of variable definition:

Column name Description
Country_code International Country code (ISO 3166-1-Alpha-2 code elements)
Country country name
Format_name Name of guideline (e.g., IPCC Common Reporting Format)
Pollutant_name Short name of pollutant (CO2, CH4, All greenhouse gases - (CO2 equivalent), Unspecified mix of HFCs and PFCs - (CO2 equivalent), HFCs - (CO2 equivalent), SF6 - (CO2 equivalent), N2O, NF3 - (CO2 equivalent), PFCs - (CO2 equivalent))
Sector_code Sector code (e.g., 1,1.A.1.b, Sectors/Totals_excl…)
Sector_name Sector name (e.g., Total (without LULUCF),5 - Waste management, 2 - Industrial Processes and Product Use…)
Parent_sector_code Parent sector code (e.g., 1,4.A, 2.B…)
Unit Unit of the measure value (Gg CO2 equivalent)
Year Year (1985-2018)
emissions Emission value
Notation Notation key
PublicationDate Publication Date

5.1.1.2 Data Mapping

OGS.MAP.EEA = function(eea_data, geoscale, geoname.filter, sector.filter, gas.filter){
  eea_data_OGS = eea_data %>% 
    # recode sectors and gas values
    mutate(sector = fct_collapse(Sector_name, "All" = "Total (with LULUCF)"),
           gas = fct_collapse(Pollutant_name, "All" = "All greenhouse gases - (CO2 equivalent)")) %>% 
    # rename columns
    add_column(data.provider = "EEA",
               geo.scale = geoscale,
               geo.code.iso3c = NA,
               unit = "MtCO₂e") %>% 
    rename(data.source = DataSource,
           geo.code.iso2c = Country_code,
           geo.name = Country,
           value = emissions,
           year = Year) %>% 
    select(data.source, data.provider, geo.scale, geo.code.iso2c, geo.code.iso3c, geo.name,
           year, sector, gas, value) %>% 
    # filter
    filter(geo.name == geoname.filter & sector == sector.filter & gas == gas.filter) %>% 
    mutate_at("value" , as.numeric) %>% 
    mutate_at("year" , as.numeric) %>% 
    mutate(value = value * 0.001) %>% 
    arrange(year)
  
  return(eea_data_OGS)
}


eea_data_OGS_fr = OGS.MAP.EEA(ghg_emissions_eea,
                              geoscale = "Country",
                              geoname.filter = "France",
                              sector.filter = "All",
                              gas.filter = "All")

# plot timeserie

eea_data_OGS_fr %>% 
  plot_ly() %>% 
  add_trace(y = ~value, 
            x = ~year, 
            color = ~data.provider,
            type = 'scatter',
            # type = "line",
            mode = 'lines+markers',
            orientation = "v",
            hoverinfo = 'text',
            text = ~paste('</br> Year: ', year,
                          '</br> Value: ', value,
                          '</br> Gas: ', gas,
                          '</br> Sector: ', sector,
                          '</br> Source: ', data.provider)) %>% 
  layout(title = "France -  GHG emissions (source: EEA)",
         yaxis = list(title = "GHG emissions (MtCO₂)"), 
         xaxis = list(title = "Years"))

5.1.2 The World Bank

Worldbank_data_OGS_fr = OGS.MAP.WB(Worldbank_data = ghg_emissions_wb,
                                start_date = 1970,
                                end_date = 2012,
                                geoscale = "Country",
                                geoname.filter = "France" )

# plot timeserie
Worldbank_data_OGS_fr %>% 
  plot_ly() %>% 
  add_trace(y = ~value, 
            x = ~year, 
            type = 'scatter',
            mode = 'lines+markers',
            orientation = "v",
            hoverinfo = 'text',
            text = ~paste('</br> Year: ', year,
                          '</br> Value: ', value,
                          '</br> Gas: ', gas,
                          '</br> Sector: ', sector,
                          '</br> Source: ', data.provider)) %>% 
  layout(title = "France -  GHG emissions (source: Wrold Bank)",
         yaxis = list(title = "GHG emissions"), 
         xaxis = list(title = "Years"))

5.1.3 The World resources Institute - CAIT

wri_CAIT_data_OGS_fr = OGS.MAP.WRI.CAIT(wri_data = ghg_emissions_wri,
                                datasource.filter = "CAIT",
                                geoname.filter = "France",
                                gas.filter = "All",
                                sector.filter = "All",
                                geoscale = "World",
                                start_date = 1990,
                                end_date = 2016)

# plot timeserie
wri_CAIT_data_OGS_fr %>% 
  plot_ly() %>% 
  add_trace(y = ~value, 
            x = ~year, 
            type = 'scatter',
            mode = 'lines+markers',
            orientation = "v",
            hoverinfo = 'text',
            text = ~paste('</br> Year: ', year,
                          '</br> Value: ', value,
                          '</br> Gas: ', gas,
                          '</br> Sector: ', sector,
                          '</br> Source: ', data.provider)) %>% 
  layout(title = "France GHG emissions (source: WRI - CAIT)",
         yaxis = list(title = "GHG emissions"), 
         xaxis = list(title = "Years"))

5.1.4 The World resources Institute - UNFCCC

OGS.MAP.WRI.UNFCCC = function(wri_data, start_date, end_date, geoscale,sector.filter,gas.filter,geoname.filter,datasource.filter){
  wri_UNFCCC_data_OGS = wri_data %>% 
    filter(Data.source == datasource.filter,
           Country == geoname.filter)%>% 
    # recode sectors and gas values
    mutate(sector = fct_collapse(Sector, "All" = "Total GHG emissions with LULUCF"),
           gas = fct_collapse(Gas, "All" = "Aggregate GHGs")) %>% 
    # filter gas and sector
    filter(sector == sector.filter,
           gas == gas.filter) %>% 
    # pivot data
    pivot_longer(
      cols = starts_with("X"), 
      names_to = "year",
      names_prefix = "X",
      values_to = "value") %>% 
    mutate_at("year" , as.numeric) %>% 
    arrange(year) %>% 
    add_column(data.provider = "WRI.UNFCCC",
               geo.scale = geoscale,
               geo.code.iso3c = NA,
               geo.code.iso2c = NA,
               unit = "MtCO₂e") %>% 
    rename(data.source = Data.source,
           geo.name = Country,
           value = value) %>% 
    select(data.source, data.provider, geo.scale, geo.code.iso2c, geo.code.iso3c, geo.name,
           year, sector, gas, value) %>% 
    filter(year >= start_date & year <= end_date) %>% 
    mutate_at("value" , as.numeric) 
  
  return(wri_UNFCCC_data_OGS)
}


wri_UNFCCC_data_OGS_fr = OGS.MAP.WRI.UNFCCC(wri_data = ghg_emissions_wri,
                                datasource.filter = "UNFCCC_AI",
                                geoname.filter = "France",
                                gas.filter = "All",
                                sector.filter = "All",
                                geoscale = "Country",
                                start_date = 1990,
                                end_date = 2016)

# plot timeserie
wri_UNFCCC_data_OGS_fr %>% 
  plot_ly() %>% 
  add_trace(y = ~value, 
            x = ~year, 
            type = 'scatter',
            mode = 'lines+markers',
            orientation = "v",
            hoverinfo = 'text',
            text = ~paste('</br> Year: ', year,
                          '</br> Value: ', value,
                          '</br> Gas: ', gas,
                          '</br> Sector: ', sector,
                          '</br> Source: ', data.provider)) %>% 
  layout(title = "France GHG emissions (source: WRI - UNFCCC)",
         yaxis = list(title = "GHG emissions"), 
         xaxis = list(title = "Years"))

5.1.5 CITEPA

Created in 1961, CITEPA (Technical Reference for Air Pollution and Climate Change) quantifies, identifies, expertises and reports atmospheric emissions data, explanatory variables and efficiency indicators, as well as methods for monitoring, quantifying, projecting and modeling emissions, policies and measures of mitigation and adaptation.

As a non-profit organisation and State operator for the French Environment Ministry, the Citepea meets reporting requirements for air pollutants and greenhouse gas emissions from France in different inventory formats, such as UNFCCC, EMEP, and Kyoto Protocol.

Data:

Citepa officially estimates greenhouse gas and air polluant emissions each year on behalf of the Ministry of the Environment. his inventory is carried out as part of France’s international commitments, mainly under the United Nations Framework Convention on Climate Change (as well as the Kyoto Protocol and the Paris Agreement) for greenhouse gases, and the United Nations Economic Commission for Europe for pollutants (LRTAP Convention).

All produced data and official reports can be download from this page.

https://www.data.gouv.fr/fr/datasets/inventaire-de-gaz-a-effet-de-serre-territorialise/

5.2 Data compilation

In this section we will combine the different data sources in order to compare ghg emissions’ values

# combine data sources
OGS_ghg_emission_fr = bind_rows(Worldbank_data_OGS_fr, 
                                wri_CAIT_data_OGS_fr,
                                wri_UNFCCC_data_OGS_fr,
                                eea_data_OGS_fr)

# plot timeserie
OGS_ghg_emission_fr %>% 
  filter(year >= 1990) %>%
  plot_ly() %>% 
  add_trace(y = ~value, 
            x = ~year, 
            color = ~data.provider,
            type = 'scatter',
            # type = "line",
            mode = 'lines+markers',
            orientation = "v",
            hoverinfo = 'text',
            text = ~paste('</br> Year: ', year,
                          '</br> Value: ', value,
                          '</br> Gas: ', gas,
                          '</br> Sector: ', sector,
                          '</br> Source: ', data.provider)) %>% 
  layout(title = "France GHG emissions",
         yaxis = list(title = "GHG emissions (MtCO₂)"), 
         xaxis = list(title = "Years"))

6 Sub-national scale: France use case

6.1 Introduction

GHG reporting for sub-national territories may refer to multiple geographical divisions such as: municipalities, districts, regions… Different approaches may be undertaken for assessing carbon footprint of territories:

  • Spatial inventory of GHG emissions: It refers to national methods used under Kyoto Protocol applied at the territorial level; It covers direct emissions and Scope 2 emissions. Examples of frameworks: OMINEA
  • Holistic approach: It consists of assessing all the emissions produced by territory activity, including direct and indirect emissions. Examples of frameworks: Bilan Carbone® Territoire; Global Protocol for Community…
  • Consumption approach: It refers to assessing all emissions ,ecessary for inhabitants in a territory, including direct and indirect emissions from importation.

ADEME provides in this article a comprehensive comparison of these different approaches for GHG assessment.

6.2 Data sources

6.2.1 ADEME - BEGES

6.2.1.1 Data exploration

6.2.1.2 Data mapping

6.2.2 CITEPA - IGT

6.2.2.1 Data exploration

citepa_IGT = read.csv(file ="https://raw.githubusercontent.com/OpenGeoScales/CarbonData/main/datasets/raw/citepa/igt/IGT%20-%20Pouvoir%20de%20r%C3%A9chauffement%20global-full.csv",
                                   encoding = "UTF-8")

citepa_IGT_OGS = citepa_IGT %>% 
  mutate(Total_emissions = rowSums(.[3:12], na.rm = TRUE))
  

# plot map of vulnerability index

library(leaflet)
library(RColorBrewer)

pal <- colorQuantile(palette = "RdYlBu", n = 5,
                     domain = citepa_IGT_OGS$Total_emissions,
                     reverse = TRUE)

labels <- sprintf(
  "<strong>%s</strong><br/><strong>%s</strong><br/>",
  paste("Name", citepa_IGT_OGS$Commune, sep=": "), 
  paste("Total emissions", round(citepa_IGT_OGS$Total_emissions,2), sep =": ")
) %>% 
  lapply(htmltools::HTML)

leaflet(data = citepa_IGT_OGS, height = 400, width = "100%") %>% 
  addTiles() %>%
  addProviderTiles(providers$CartoDB.DarkMatter) %>% 
  addCircleMarkers(~lon, ~lat, 
                   radius = 1,
                   color = ~pal(Total_emissions),
                   stroke = FALSE,
                   fillOpacity = 0.7,
                   weight = 100,
                   popup = ~as.character(Commune), 
                   label = labels) %>% 
  addLegend(pal = pal, values = ~Total_emissions, opacity = 0.9, 
            title = "Total emissions",
            position = "bottomright",
            labFormat = labelFormat(suffix = " "))

6.2.2.2 Data mapping

6.3 Data compilation